nebulous/cloud-fog-service-broker
Code Issues Proposed changes

Use env vars in front and back end projects

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Change-Id: Id093976032f079c62efd9fcaaf0617e05ceef3b0
This commit is contained in:
jmarchel 2024-03-22 14:05:38 +01:00 committed by Radosław Piliszek
parent ac6e1c1300
commit 40d9f11047
43 changed files with 5220 additions and 1039 deletions
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2
cfsb-backend/.env.prod
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@ -2,7 +2,7 @@ NEBULOUS_BROKER_URL=158.37.63.86
NEBULOUS_BROKER_PORT=31609
NEBULOUS_BROKER_USERNAME=admin
NEBULOUS_BROKER_PASSWORD=admin
POSTGRES_DB_HOST=localhost
POSTGRES_DB_HOST=db
POSTGRES_DB_NAME=fog_broker
POSTGRES_DB_PORT=5432
POSTGRES_DB_USER=dbuser

0
cfsb-backend/API_Functions.py
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28
cfsb-backend/Evaluation.py
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@ -6,7 +6,7 @@ from scipy.stats import rankdata
def perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_names, node_ids):
print("Evaluation begun with perform_evaluation():")
# print("Data Table:", data_table)
# Identify the boolean criteria columns by checking if all values are either 0 or 1
# Identify the boolean criteria columns by checking if all values are either 0 or 1
# boolean_criteria = [criterion for criterion in data_table if set(data_table[criterion]) <= {0, 1}]
boolean_criteria = [criterion for criterion in data_table if 'boolean' in criterion.lower()]
# print("Boolean Criteria:", boolean_criteria)
@ -18,10 +18,10 @@ def perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_nam
# The first category is for the all False and the last for the all True values
fog_node_categories = {i: [] for i in range(len(boolean_criteria) + 1)}
# Iterate over the list of fog nodes to count the '1' (True) values and assign categories
for i in range(len(node_names)):
# Iterate over the list of nodes to count the '1' (True) values and assign categories
for i in range(len(node_ids)):
true_count = sum(data_table[boolean][i] for boolean in boolean_criteria)
fog_node_categories[true_count].append(node_names[i])
fog_node_categories[true_count].append(node_ids[i])
# Remove the boolean criteria from the data_table
for boolean in boolean_criteria:
@ -41,8 +41,8 @@ def perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_nam
for fog_node_high in fog_node_categories[sorted_categories[higher_cat]]:
for fog_node_low in fog_node_categories[sorted_categories[higher_cat + 1]]:
# Create a constraint for each pair of fog nodes (high > low)
high_scores = [-data_table[criterion][node_names.index(fog_node_high)] for criterion in data_table]
low_scores = [-data_table[criterion][node_names.index(fog_node_low)] for criterion in data_table]
high_scores = [-data_table[criterion][node_ids.index(fog_node_high)] for criterion in data_table]
low_scores = [-data_table[criterion][node_ids.index(fog_node_low)] for criterion in data_table]
constraint = [h - l for h, l in zip(high_scores, low_scores)]
A_boolean.append(constraint)
b_boolean.append(0) # The score difference must be greater than 0
@ -124,8 +124,8 @@ def perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_nam
num_of_dmus = len(next(iter(data_table.values())))
Cols_No = len(criteria_list)
DEA_Scores = []
epsilon = 0.00000 # Lower bound of the variables
# epsilon = 0.000001 # Lower bound of the variables
epsilon = 0
# Iterating over each DMU to Perform DEA
for dmu_index in range(num_of_dmus):
# Gathering values for the current DMU
@ -171,7 +171,7 @@ def perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_nam
"DEA Score": DEA_Scores[i],
"Rank": int(DEA_Scores_Ranked[i])
}
for i in range(len(node_names))
for i in range(len(node_ids))
]
# Return successful results
@ -184,9 +184,9 @@ def perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_nam
# relative_wr_data: [{'LHSCriterion': 'Accountability', 'Operator': 1, 'Intense': 2, 'RHSCriterion': 'Compliance'}]
# immediate_wr_data: [{'Criterion': 'Compliance', 'Operator': 1, 'Value': 0.5}]
#
# node_names = ['2ad4bd97-d932-42a5-860e-e607a50f161d', 'e917581d-1a62-496b-9d2e-05972fe309e9', '78aca9a8-8c14-4c7d-af34-72cef0da992d', 'd2bddce9-4118-41a9-b528-3bac32b13312']
# node_ids = ['2ad4bd97-d932-42a5-860e-e607a50f161d', 'e917581d-1a62-496b-9d2e-05972fe309e9', '78aca9a8-8c14-4c7d-af34-72cef0da992d', 'd2bddce9-4118-41a9-b528-3bac32b13312']
#
# Evaluation_JSON = perform_evaluation(data_table, [], [], node_names)
# Evaluation_JSON = perform_evaluation(data_table, [], [], node_ids)
# pretty_json = json.dumps(Evaluation_JSON)
@ -218,13 +218,13 @@ def perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_nam
# # # "immediate_wr_data":[{"Criterion":"Accountability","Operator":1,"Value":0.2}]}
# # # w1>=0.2 and w1<=0.5
# #
# node_names = ['Fog Node 1', 'Fog Node 2', 'Fog Node 3', 'Fog Node 4', 'Fog Node 5']
# node_ids = ['Fog Node 1', 'Fog Node 2', 'Fog Node 3', 'Fog Node 4', 'Fog Node 5']
#
# Evaluation_JSON = perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_names)
# Evaluation_JSON = perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_ids)
# print("Evaluation_JSON:", Evaluation_JSON)
# Evaluation_JSON = perform_evaluation(data_table, [], [], node_names)
# Evaluation_JSON = perform_evaluation(data_table, [], [], node_ids)
# pretty_json = json.dumps(Evaluation_JSON)
# print(pretty_json)
# print("Evaluation_JSON:", Evaluation_JSON)

666
cfsb-backend/User_Functions.py
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@ -1,12 +1,8 @@
import os
# import read_file
import get_data as file
import random
import json
from datetime import datetime
import data_types as attr_data_types
from Evaluation import perform_evaluation
from data_types import get_attr_data_type
import db.db_functions as db_functions
# Boolean_Variables = ['Extend offered network capacity', 'Extend offered processing capacity', 'Extend offered memory capacity',
@ -16,48 +12,93 @@ Boolean_Variables = [
"0cf00a53-fd33-4887-bb38-e0bbb04e3f3e", "d95c1dae-1e22-4fb4-9cdc-743e96d0dddc",
"8cd09fe9-c119-4ccd-b651-0f18334dbbe4", "7147995c-8e68-4106-ab24-f0a7673eb5f5", "c1c5b3c9-6178-4d67-a7e3-0285c2bf98ef"]
# Used to transform SAL's response before sending to DataGrid
# This version is designed to read the structure of SAL's response obtained from POSTMAN
def extract_node_candidate_data(json_file_path):
with open(json_file_path, 'r') as file:
json_data = json.load(file)
# Used to extract_SAL_node_candidate_data from Use Side for DataGrid
def extract_SAL_node_candidate_data_Front(json_data):
default_criteria_list = ["cores", "ram", "disk", "memoryPrice", "price"]
if isinstance(json_data, dict): # Single node dictionary
json_data = [json_data] # Wrap it in a list
extracted_data = []
node_ids = []
node_names = []
for item in json_data:
hardware_info = item.get("nodeCandidate", {}).get("hardware", {})
hardware_info = item.get("hardware", {})
# Extract default criteria values
default_criteria_values = {criteria: hardware_info.get(criteria, 0.0) if criteria in hardware_info else item.get(criteria, 0.0) for criteria in default_criteria_list}
# Correctly extract the providerName from the cloud information
cloud_info = item.get("cloud", {}) # get the cloud info or default to an empty dict
api_info = cloud_info.get("api", {})
provider_name = api_info.get("providerName", "Unknown Provider")
# each item is now a dictionary
node_data = {
"name": item['name'],
"id": item['id'],
"nodeId": item.get("nodeCandidate", {}).get("nodeId"),
"nodeCandidateType": item.get("nodeCandidate", {}).get("nodeCandidateType"),
"price": item.get("nodeCandidate", {}).get("price", 0.0),
"pricePerInvocation": item.get("nodeCandidate", {}).get("pricePerInvocation", 0.0),
"memoryPrice": item.get("nodeCandidate", {}).get("memoryPrice", 0.0),
"hardware": {
"id": hardware_info.get("id"),
"name": hardware_info.get("name"),
"providerId": hardware_info.get("providerId"),
"cores": hardware_info.get("cores"),
"ram": hardware_info.get("ram") * 1024 if hardware_info.get("ram") else None, # Assuming RAM needs conversion from GB to MB
"disk": hardware_info.get("disk"),
"fpga": hardware_info.get("fpga")
}
"nodeId": item.get("nodeId", ''),
"id": item.get('id', ''),
"nodeCandidateType": item.get("nodeCandidateType", ''),
**default_criteria_values, # Unpack default criteria values into node_data
"hardware": hardware_info,
"location": item.get("location", {}),
"image": item.get("image", {}),
"providerName": provider_name
}
extracted_data.append(node_data)
node_ids.append(item['id'])
node_names.append(item.get('name', ''))
node_ids.append(node_data["id"])
number_of_nodes = len(json_data)
# print("Before create_node_name")
node_names.append(create_node_name(node_data)) # call create_node_name function
# print("After create_node_name")
return extracted_data, number_of_nodes, node_ids, node_names
return extracted_data, node_ids, node_names
# Used to create node names for DataGrid
def create_node_name(node_data):
node_type = node_data.get("nodeCandidateType", "UNKNOWN_TYPE")
# Initialize default values
node_city = ""
node_country = ""
node_os_family = "Unknown OS"
provider_name = node_data.get("providerName", "")
# Only 50 nodes
# Safely access nested properties for city and country
location = node_data.get("location")
if location and "geoLocation" in location and location["geoLocation"]:
geo_location = location["geoLocation"]
node_city = geo_location.get("city", "")
node_country = geo_location.get("country", "")
image = node_data.get("image")
if image and "operatingSystem" in image and image["operatingSystem"]:
operating_system = image["operatingSystem"]
node_os_family = operating_system.get("operatingSystemFamily", node_os_family)
cores = node_data.get("cores", "")
ram = node_data.get("ram", "")
# Construct the node name with conditional inclusions
node_name_parts = [node_type]
if node_city and node_country:
node_name_parts.append(f"{node_city}, {node_country}")
if provider_name:
node_name_parts.append(f"Provider: {provider_name}")
node_name_parts.append(f"OS: {node_os_family}")
if cores:
node_name_parts.append(f"Cores: {cores} ")
if ram:
node_name_parts.append(f"RAM: {ram} ")
node_name = " - ".join(part for part in node_name_parts if part) # Only include non-empty parts
return node_name
# Used to extract_SAL_node_candidate_data from App Side working with Optimizer
def extract_SAL_node_candidate_data(json_string):
# print("Entered in extract_SAL_node_candidate_data")
try:
json_data = json.loads(json_string) # Ensure json_data is a list of dictionaries
except json.JSONDecodeError as e:
@ -73,9 +114,9 @@ def extract_SAL_node_candidate_data(json_string):
"nodeId": item.get("nodeId", ''),
"id": item.get('id', ''),
"nodeCandidateType": item.get("nodeCandidateType", ''),
"price": item.get("price", 0.0),
"pricePerInvocation": item.get("pricePerInvocation", 0.0),
"memoryPrice": item.get("memoryPrice", 0.0),
"price": item.get("price", ''),
"pricePerInvocation": item.get("pricePerInvocation", ''),
"memoryPrice": item.get("memoryPrice", ''),
"hardware": item.get("hardware", {})
}
extracted_data.append(node_data)
@ -85,48 +126,11 @@ def extract_SAL_node_candidate_data(json_string):
number_of_nodes = len(extracted_data)
node_ids = [node['id'] for node in extracted_data]
node_names = [node['id'] for node in extracted_data]
return extracted_data, number_of_nodes, node_ids, node_names
# Used to transform SAL's response all nodes
# def extract_SAL_node_candidate_data(sal_reply):
# # Parse the JSON string in the body of the SAL reply
# body = sal_reply.get('body', '')
# extracted_data = []
#
# try:
# json_data = json.loads(body)
# except json.JSONDecodeError as e:
# print(f"Error parsing JSON: {e}")
# return extracted_data
#
# for item in json_data:
# node_data = {
# "name": item.get('name', ''),
# "name": item.get('id', ''),
# "id": item.get('id', ''),
# "nodeId": item.get("nodeId", ''),
# "nodeCandidateType": item.get("nodeCandidateType", ''),
# "price": item.get("price", 0.0),
# "pricePerInvocation": item.get("pricePerInvocation", 0.0),
# "memoryPrice": item.get("memoryPrice", 0.0),
# "hardware": item.get("hardware", {})
# }
# extracted_data.append(node_data)
#
# number_of_nodes = len(extracted_data)
# node_ids = [node['id'] for node in extracted_data]
# node_names = [node['name'] for node in extracted_data]
# if not node_names:
# node_names = node_ids
#
# return extracted_data, number_of_nodes, node_ids, node_names
return extracted_data, node_ids, node_names
# Used to map the criteria from SAL's response with the selected criteria (from frontend)
def create_criteria_mapping(selected_items, extracted_data):
def create_criteria_mapping():
field_mapping = {
# "Cost": "price",
"Operating cost": "price",
@ -137,7 +141,8 @@ def create_criteria_mapping(selected_items, extracted_data):
}
return field_mapping
# Used to create the required structure for the Evaluation
# Used to create the required structure for the Evaluation in process_evaluation_data endpoint
def transform_grid_data_to_table(json_data):
grid_data = json_data.get('gridData', [])
relative_wr_data = json_data.get('relativeWRData', [])
@ -153,8 +158,9 @@ def transform_grid_data_to_table(json_data):
boolean_value_mapping = {"True": 1, "False": 0}
for node in grid_data:
node_name = node.get('name')
# node_name = node.get('name')
node_ids.append(node.get('id'))
node_id = node.get('id')
criteria_data = {}
for criterion in node.get('criteria', []):
@ -177,7 +183,7 @@ def transform_grid_data_to_table(json_data):
# Handle or log the error for values that can't be converted to float
pass
temp_data_table[node_name] = criteria_data
temp_data_table[node_id] = criteria_data
# Collect all criteria titles
criteria_titles.extend(criteria_data.keys())
@ -189,7 +195,7 @@ def transform_grid_data_to_table(json_data):
data_table = {title: [] for title in criteria_titles}
# Populate the final data table
for node_name, criteria_data in temp_data_table.items():
for node_id, criteria_data in temp_data_table.items():
for title, value in criteria_data.items():
data_table[title].append(value)
@ -254,64 +260,6 @@ def check_json_file_exists(app_id):
return os.path.exists(file_path)
# Used to read ALL the saved Data for an Application
# def read_application_data(app_id):
# # Directory path and file path
# app_dir = os.path.join("app_dirs", app_id)
# file_path = os.path.join(app_dir, "data.json")
#
# # Check if the file exists
# if os.path.exists(file_path):
# # Read and parse the JSON file
# with open(file_path, 'r', encoding='utf-8') as f:
# data = json.load(f)
# # Extract specific parts of the data
# # selected_criteria = data.get("selectedCriteria", None)
# data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = transform_grid_data_to_table(data)
# else:
# print(f"No data found for application ID {app_id}.") # Return everything empty
# data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = [], [], [], [], []
#
# return data_table, relative_wr_data, immediate_wr_data, node_names, node_ids
# Used to read the saved Data of the Application ONLY for the Nodes returned by SAL
def read_application_data(app_id, node_ids_SAL):
# Directory path and file path
app_dir = os.path.join("app_dirs", app_id)
file_path = os.path.join(app_dir, f"{app_id}_data.json")
# Initialize variables to return in case of no data or an error
data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = [], [], [], [], []
# Check if the file exists
if os.path.exists(file_path):
# Read and parse the JSON file
with open(file_path, 'r', encoding='utf-8') as f:
data = json.load(f)
# Filter gridData based on node_ids_SAL
filtered_grid_data = [node for node in data['gridData'] if node['id'] in node_ids_SAL]
# Create a new JSON structure with filtered gridData
filtered_json_data = {
"gridData": filtered_grid_data,
"relativeWRData": data['relativeWRData'],
"immediateWRData": data['immediateWRData'],
"nodeNames": [node['name'] for node in filtered_grid_data], # Assuming you want to filter nodeNames as well
"nodeIds": node_ids_SAL # Assuming you want to include nodeIds from the filtered list
}
# Call transform_grid_data_to_table with the new filtered JSON data
data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = transform_grid_data_to_table(filtered_json_data)
else:
print(f"No data found for application ID {app_id}.")
return data_table, relative_wr_data, immediate_wr_data, node_names
#Used to create data table from SAL's response in app_side
def create_data_table(selected_criteria, extracted_data, field_mapping):
# Initialize the data table with lists for each criterion
data_table = {criterion: [] for criterion in selected_criteria}
@ -339,59 +287,23 @@ def create_data_table(selected_criteria, extracted_data, field_mapping):
return data_table
import random
# def append_evaluation_results(sal_reply_body, scores_and_ranks):
# # Check if sal_reply_body is a string and convert it to a Python object
# if isinstance(sal_reply_body, str):
# sal_reply_body = json.loads(sal_reply_body)
#
# if scores_and_ranks:
# # Create a dictionary mapping Ids to scores and ranks
# eval_results_dict = {result['Id']: (result['DEA Score'], result['Rank'])
# for result in scores_and_ranks}
#
# # Iterate over each node in sal_reply_body and append Score and Rank
# for node in sal_reply_body:
# node_id = node.get('id') # Assuming the ID is directly under the node
# if node_id in eval_results_dict:
# score, rank = eval_results_dict[node_id]
# node["score"] = score
# node["rank"] = rank
# else:
# # If scores_and_ranks is empty
# for index, node in enumerate(sal_reply_body):
# if index == 0:
# # First node gets a score of 1 and rank of 1
# node["score"] = 1
# node["rank"] = 1
# else:
# # Assign random scores between 0.33 and 0.93 to the rest
# node["score"] = random.uniform(0.33, 0.93)
#
# # Sort nodes by score in descending order to calculate ranks
# sorted_nodes = sorted(sal_reply_body[1:], key=lambda x: x["score"], reverse=True)
#
# # Assign ranks based on sorted order, starting from 2 since the first node is ranked 1
# for rank, node in enumerate(sorted_nodes, start=2):
# node["rank"] = rank
#
# # Combine the first node with the rest
# sal_reply_body = [sal_reply_body[0]] + sorted_nodes
#
# return sal_reply_body
# Used to Append "Score" and "Rank" for each node in SAL's response JSON
def append_evaluation_results(sal_reply_body, scores_and_ranks):
# Check if sal_reply_body is a string and convert it to a Python object
if isinstance(sal_reply_body, str):
sal_reply_body = json.loads(sal_reply_body)
# Check if there is only one node and scores_and_ranks are empty
if len(sal_reply_body) == 1 and not scores_and_ranks:
# Directly assign score and rank to the single node
sal_reply_body[0]["score"] = 1
sal_reply_body[0]["rank"] = 1
return sal_reply_body
# Proceed if there are multiple nodes or scores_and_ranks is not empty
# Create a dictionary mapping Ids to scores and ranks
eval_results_dict = {result['Id']: (result['DEA Score'], result['Rank'])
for result in scores_and_ranks}
for result in scores_and_ranks if scores_and_ranks}
# Iterate over each node in sal_reply_body and append Score and Rank
for node in sal_reply_body:
@ -404,37 +316,387 @@ def append_evaluation_results(sal_reply_body, scores_and_ranks):
return sal_reply_body
def convert_value(value, criterion_info, is_matched):
if criterion_info['type'] == 5: # Boolean type
return 1 if value else 0
elif criterion_info['type'] == 1: # Ordinal type
if is_matched: # For matched nodes, use the mapping
ordinal_value_mapping = {"High": 3, "Medium": 2, "Low": 1}
return ordinal_value_mapping.get(value, value) # Use the value from mapping, or keep it as is if not found
else: # For unmatched nodes, assign default value
return 1
return value
# Used to read the saved application data CFSB when triggered by Optimizer
def read_application_data(app_id, sal_reply_body):
app_dir = os.path.join("app_dirs", app_id)
file_path = os.path.join(app_dir, f"{app_id}_data.json")
data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = {}, [], [], [], []
if isinstance(sal_reply_body, str):
sal_reply_body = json.loads(sal_reply_body)
if os.path.exists(file_path):
print(f"JSON file found for application ID {app_id}.")
with open(file_path, 'r', encoding='utf-8') as f:
data = json.load(f)
selected_criteria = {criterion['title']: criterion for criterion in data.get('selectedCriteria', [])}
# Define the default list criteria mapping
default_list_criteria_mapping = {
"Operating cost": "price",
"Memory Price": "memoryPrice",
"Number of CPU Cores": "cores",
"Memory Size": "ram",
"Storage Capacity": "disk"
}
for criterion in selected_criteria:
data_table[criterion] = []
matched_node_ids = [node['id'] for node in data.get('gridData', []) if node['id'] in [n['id'] for n in sal_reply_body]]
unmatched_node_ids = [n['id'] for n in sal_reply_body if n['id'] not in matched_node_ids]
# Process MATCHED nodes
for node in data.get('gridData', []):
if node['id'] in matched_node_ids:
node_ids.append(node['id'])
# node_names.append(node.get('name', 'Unknown'))
for crit, criterion_info in selected_criteria.items():
value = next((criterion['value'] for criterion in node['criteria'] if criterion['title'] == crit), None)
converted_value = convert_value(value, criterion_info, is_matched=True)
data_table[crit].append(converted_value)
# Process UNMATCHED nodes
for node_id in unmatched_node_ids:
node_data = next((node for node in sal_reply_body if node['id'] == node_id), {})
node_ids.append(node_id)
for criterion, crit_info in selected_criteria.items():
mapped_field = default_list_criteria_mapping.get(criterion, '')
value = node_data.get(mapped_field, 0.001 if crit_info['type'] == 2 else False)
converted_value = convert_value(value, crit_info, is_matched=False)
data_table[criterion].append(converted_value)
node_names = node_ids
relative_wr_data, immediate_wr_data = data.get('relativeWRData', []), data.get('immediateWRData', [])
else: # There is not any node id match - Proceed only with the nodes from SAL's reply
print(f"No JSON file found for application ID {app_id}. Proceed only with data from SAL.")
extracted_data_SAL, node_ids_SAL, node_names_SAL = extract_SAL_node_candidate_data(sal_reply_body)
selected_criteria = ["Number of CPU Cores", "Memory Size"]
field_mapping = create_criteria_mapping()
data_table = create_data_table(selected_criteria, extracted_data_SAL, field_mapping)
# Assign relativeWRData and immediateWRData regardless of node ID matches
relative_wr_data = []
immediate_wr_data = []
node_ids = node_ids_SAL
node_names = node_ids
return data_table, relative_wr_data, immediate_wr_data, node_names, node_ids
# Used to generate random values for DataGrid
def random_value_based_on_type(data_type, criterion_info=None):
if data_type == 1: # Ordinal
# Assuming 'values' are part of criterion_info for ordinal types
return random.choice(criterion_info.get('values', ["High", "Medium", "Low"]))
elif data_type == 5: # Boolean
return random.choice([True, False])
else: # Numeric
# Default case for numeric types
return round(random.uniform(1, 100), 2)
# Used to parse Patini's JSON
def parse_device_info_from_file(file_path):
with open(file_path, 'r') as file:
json_data = json.load(file)
device_names = []
device_info = {
'id': json_data['_id'],
'name': json_data['name'], # Save the device name
'deviceInfo': json_data['deviceInfo'],
'creationDate': json_data['creationDate'],
'lastUpdateDate': json_data['lastUpdateDate'],
'status': json_data['status'],
'metrics': {
'cpu': json_data['metrics']['metrics']['cpu'],
'uptime': json_data['metrics']['metrics']['uptime'],
'disk': json_data['metrics']['metrics']['disk'],
'ram': json_data['metrics']['metrics']['ram']
}
}
# Example of converting and handling ISODate strings, adjust accordingly
device_info['creationDate'] = datetime.fromisoformat(device_info['creationDate'].replace("ISODate('", "").replace("')", ""))
device_info['lastUpdateDate'] = datetime.fromisoformat(device_info['lastUpdateDate'].replace("ISODate('", "").replace("')", ""))
device_info['creationDate'] = device_info['creationDate'].isoformat()
device_info['lastUpdateDate'] = device_info['lastUpdateDate'].isoformat()
# Update the global device_names list
device_names.append({'id': device_info['id'], 'name': device_info['name']})
return device_names, device_info
#---------------Read Application Data
# Example usage
# extracted_data, NUMBER_OF_FOG_NODES, node_names = extract_node_candidate_data('dummy_data_node_candidates.json')
# print(NUMBER_OF_FOG_NODES)
# print(node_names)
# app_id = 'd535cf554ea66fbebfc415ac837a5828'
# data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = read_app_specific_data(app_id)
# Used to read the saved Data of the Application ONLY for the Nodes returned by SAL
# def read_application_data(app_id, sal_reply_body):
# # Directory path and file path
# app_dir = os.path.join("app_dirs", app_id)
# file_path = os.path.join(app_dir, f"{app_id}_data.json")
#
# print("Node Names:", node_names)
# print("data_table:", data_table)
# print("Relative WR Data:", relative_wr_data)
# print("Immediate WR Data:", immediate_wr_data)
# # Initialize variables to return in case of no data or an error
# data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = [], [], [], [], []
# # Read data from SAL's reply
# extracted_data_SAL, node_ids_SAL, node_names_SAL = extract_SAL_node_candidate_data(sal_reply_body)
#
# evaluation_results = perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_names, node_ids)
# print("evaluation_results:", evaluation_results)
# # Check if the file exists
# if os.path.exists(file_path):
# # Read and parse the JSON file
# with open(file_path, 'r', encoding='utf-8') as f:
# data = json.load(f)
#
# # Extracting the results and saving them into a variable
# ScoresAndRanks = evaluation_results['results']
# print("ScoresAndRanks:", ScoresAndRanks)
# # Filter gridData based on Nodes returned by SAL
# filtered_grid_data = [node for node in data.get('gridData', []) if node.get('id') in node_ids_SAL]
#
# if filtered_grid_data: # if there's at least 1 match
# # Create a new JSON structure and call transform_grid_data_to_table
# filtered_json_data = {
# "gridData": filtered_grid_data,
# "relativeWRData": relative_wr_data,
# "immediateWRData": immediate_wr_data,
# "nodeNames": [node.get('name') for node in filtered_grid_data],
# "nodeIds": node_ids_SAL
# }
#
# # Call transform_grid_data_to_table with the filtered JSON data
# # data_table, _, _, node_names, _ = transform_grid_data_to_table(filtered_json_data)
# data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = transform_grid_data_to_table(filtered_json_data)
# if not node_names:
# node_names = node_ids
#
# else: # There is not any node id match - Proceed only with the nodes from SAL's reply
# print("No matching node IDs found in the saved data. Proceed only with data from SAL")
# selected_criteria = ["Number of CPU Cores", "Memory Size"]
# field_mapping = create_criteria_mapping(selected_criteria, extracted_data_SAL)
# data_table = create_data_table(selected_criteria, extracted_data_SAL, field_mapping)
# # Assign relativeWRData and immediateWRData regardless of node ID matches
# relative_wr_data = []
# immediate_wr_data = []
# node_ids = node_ids_SAL
# node_names = node_ids
# if not node_names_SAL:
# node_names = node_ids
# else:
# print(f"No JSON file found for application ID {app_id}.")
#
# # Note: relative_wr_data and immediate_wr_data are returned regardless of the node IDs match
# return data_table, relative_wr_data, immediate_wr_data, node_names, node_ids
# append_evaluation_results('SAL_Response_11EdgeDevs.json', ScoresAndRanks)
#Used to create data table from SAL's response in app_side
# def read_application_data(app_id, sal_reply_body):
# app_dir = os.path.join("app_dirs", app_id)
# file_path = os.path.join(app_dir, f"{app_id}_data.json")
# data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = {}, [], [], [], []
#
# default_list_criteria_mapping = {
# "Operating cost": "price",
# "Memory Price": "memoryPrice",
# "Number of CPU Cores": "cores",
# "Memory Size": "ram",
# "Storage Capacity": "disk"
# }
#
# if isinstance(sal_reply_body, str):
# try:
# sal_reply_body = json.loads(sal_reply_body)
# except json.JSONDecodeError as e:
# print(f"Error parsing JSON: {e}")
# return data_table, relative_wr_data, immediate_wr_data, node_names, node_ids
#
# if os.path.exists(file_path):
# with open(file_path, 'r', encoding='utf-8') as f:
# data = json.load(f)
# selected_criteria = {criterion['title']: criterion for criterion in data.get('selectedCriteria', [])}
#
# for criterion in selected_criteria.keys():
# data_table[criterion] = []
#
# matched_node_ids = set(node['id'] for node in data.get('gridData', [])) & set(node['id'] for node in sal_reply_body)
# unmatched_node_ids = set(node['id'] for node in sal_reply_body) - matched_node_ids
#
# # Ordinal value mapping for MATCHED nodes
# ordinal_value_mapping = {"High": 3, "Medium": 2, "Low": 1}
#
# # Process MATCHED nodes from JSON file
# for node in data.get('gridData', []):
# if node['id'] in matched_node_ids:
# node_ids.append(node['id'])
# # node_names.append(node.get('name', 'Unknown'))
# for criterion, crit_info in selected_criteria.items():
# value = next((c['value'] for c in node['criteria'] if c['title'] == criterion), None)
# if value is not None:
# value = 1 if value is True else (0 if value is False else value)
# else: # Apply default if criterion not found
# value = 0.00001 if crit_info['type'] == 2 else 0
# data_table[criterion].append(value)
#
# # Process UNMATCHED nodes from sal_reply_body
# for node_id in unmatched_node_ids:
# node_data = next((node for node in sal_reply_body if node['id'] == node_id), {})
# node_ids.append(node_id)
# for criterion, crit_info in selected_criteria.items():
# mapped_field = default_list_criteria_mapping.get(criterion, '')
# value = node_data.get(mapped_field, 0.00001 if crit_info['type'] == 2 else False)
# value = 1 if value is True else (0 if value is False else value)
# data_table[criterion].append(value)
#
# # convert True/False to 1/0 in data_table for both boolean and string representations
# for criterion, values in data_table.items():
# data_table[criterion] = [convert_bool(value) for value in values]
# node_names = node_ids
# relative_wr_data, immediate_wr_data = data.get('relativeWRData', []), data.get('immediateWRData', [])
#
# else: # There is not any node id match - Proceed only with the nodes from SAL's reply
# print(f"No JSON file found for application ID {app_id}. Proceed only with data from SAL.")
# extracted_data_SAL, node_ids_SAL, node_names_SAL = extract_SAL_node_candidate_data(sal_reply_body)
# selected_criteria = ["Number of CPU Cores", "Memory Size"]
# field_mapping = create_criteria_mapping(selected_criteria, extracted_data_SAL)
# data_table = create_data_table(selected_criteria, extracted_data_SAL, field_mapping)
# # Assign relativeWRData and immediateWRData regardless of node ID matches
# relative_wr_data = []
# immediate_wr_data = []
# node_ids = node_ids_SAL
# node_names = node_ids
#
# return data_table, relative_wr_data, immediate_wr_data, node_names, node_ids
# Used to transform SAL's response before sending to DataGrid
# This version is designed to read the structure of SAL's response obtained from POSTMAN
def extract_node_candidate_data(json_file_path):
with open(json_file_path, 'r') as file:
json_data = json.load(file)
extracted_data = []
node_ids = []
node_names = []
for item in json_data:
hardware_info = item.get("nodeCandidate", {}).get("hardware", {})
node_data = {
"name": item['name'],
"id": item['id'],
"nodeId": item.get("nodeCandidate", {}).get("nodeId"),
"nodeCandidateType": item.get("nodeCandidate", {}).get("nodeCandidateType"),
"price": item.get("nodeCandidate", {}).get("price", 0.0),
"pricePerInvocation": item.get("nodeCandidate", {}).get("pricePerInvocation", 0.0),
"memoryPrice": item.get("nodeCandidate", {}).get("memoryPrice", 0.0),
"hardware": {
"id": hardware_info.get("id"),
"name": hardware_info.get("name"),
"providerId": hardware_info.get("providerId"),
"cores": hardware_info.get("cores"),
"ram": hardware_info.get("ram") * 1024 if hardware_info.get("ram") else None, # Assuming RAM needs conversion from GB to MB
"disk": hardware_info.get("disk"),
"fpga": hardware_info.get("fpga")
}
}
extracted_data.append(node_data)
node_ids.append(item['id'])
node_names.append(item.get('name', ''))
return extracted_data, node_ids, node_names
# Works for dummy_node_data
# def create_node_name(node_data):
# # dummy_node_data = '''{
# # "id": "8a7481d98e702b64018e702cbe070000",
# # "nodeCandidateType": "EDGE",
# # "jobIdForByon": null,
# # "jobIdForEdge": "FCRnewLight0",
# # "price": 0.0,
# # "cloud": {
# # "id": "edge",
# # "endpoint": null,
# # "cloudType": "EDGE",
# # "api": null,
# # "credential": null,
# # "cloudConfiguration": {
# # "nodeGroup": null,
# # "properties": {}
# # },
# # "owner": "EDGE",
# # "state": null,
# # "diagnostic": null
# # },
# # "location": {
# # "id": "edge-location-KmVf4xDJKL7acBGc",
# # "name": null,
# # "providerId": null,
# # "locationScope": null,
# # "isAssignable": null,
# # "geoLocation": {
# # "city": "Warsaw",
# # "country": "Poland",
# # "latitude": 52.237049,
# # "longitude": 21.017532
# # },
# # "parent": null,
# # "state": null,
# # "owner": null
# # },
# # "image": {
# # "id": "edge-image-KmVf4xDJKL7acBGc",
# # "name": "edge-image-name-UBUNTU-UNKNOWN",
# # "providerId": null,
# # "operatingSystem": {
# # "operatingSystemFamily": "UBUNTU",
# # "operatingSystemArchitecture": "UNKNOWN",
# # "operatingSystemVersion": 1804.00
# # },
# # "location": null,
# # "state": null,
# # "owner": null
# # },
# # "hardware": {
# # "id": "edge-hardware-KmVf4xDJKL7acBGc",
# # "name": null,
# # "providerId": null,
# # "cores": 1,
# # "ram": 1,
# # "disk": 1.0,
# # "fpga": 0,
# # "location": null,
# # "state": null,
# # "owner": null
# # },
# # "pricePerInvocation": 0.0,
# # "memoryPrice": 0.0,
# # "nodeId": null,
# # "environment": null
# # }'''
# # node_data = json.loads(dummy_node_data)
# # print("node_data in create node name")
# # print(node_data)
# node_type = node_data["nodeCandidateType"]
# # print(node_type)
# if node_data["location"]:
# node_location = node_data["location"]["geoLocation"]
# # print(json.dumps(node_location))
# node_city = node_location["city"]
# node_country = node_location["country"]
# else:
# node_city = ""
# node_country = ""
# node_os = node_data["image"]["operatingSystem"]["operatingSystemFamily"]
# node_name = node_type + " - " + node_city + " , " + node_country + " - " + node_os
# # print("node name crated: " + node_name)
# return node_name

252
cfsb-backend/activemq.py
View File

@ -1,8 +1,6 @@
# ActiveMQ communication logic
import sys
import threading
import json
import time
sys.path.insert(0,'../exn')
import logging
from dotenv import load_dotenv
@ -18,9 +16,10 @@ from exn.core.handler import Handler
from exn.handler.connector_handler import ConnectorHandler
from User_Functions import *
import uuid
from Evaluation import perform_evaluation
# logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
# logging.getLogger('exn.connector').setLevel(logging.CRITICAL)
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logging.getLogger('exn.connector').setLevel(logging.CRITICAL)
class SyncedHandler(Handler):
def on_message(self, key, address, body, message: Message, context=None):
@ -34,77 +33,58 @@ class SyncedHandler(Handler):
# logging.info("Entered in OPT-triggering'")
# Save the correlation_id (We do not have it from the app_side)
uuid.uuid4().hex.encode("utf-8") # for Correlation id
uuid.uuid4().hex.encode("utf-8") # for Correlation id
correlation_id_optimizer = message.correlation_id
if not correlation_id_optimizer:
correlation_id_optimizer = '88334290cad34ad9b21eb468a9f8ff11' # dummy correlation_id
# logging.info(f"Optimizer_correlation_id {message.correlation_id}")
print("Optimizer Correlation Id: ", correlation_id_optimizer)
# print("Optimizer Correlation Id: ", correlation_id_optimizer)
# application_id_optimizer = message.properties.application # can be taken also from message.annotations.application
application_id_optimizer = message.subject
# application_id_optimizer = 'd535cf554ea66fbebfc415ac837a5828' #dummy application_id_optimizer
print("Application Id: ", application_id_optimizer)
# print("Application Id: ", application_id_optimizer)
try:
# Read the Message Sent from Optimizer
opt_message_data = body
print("Whole Message Sent from Optimizer:", opt_message_data)
# print("Whole Message Sent from Optimizer:", opt_message_data)
# Extract 'body' from opt_message_data
body_sent_from_optimizer = opt_message_data.get('body', {})
# 100 Nodes
## Example body
# body_sent_from_optimizer = [
# {
# "type": "NodeTypeRequirement",
# "nodeTypes": ["IAAS"],
# "jobIdForByon": "dummy-app-id",
# "jobIdForEDGE": "dummy-app-id"
# }
# ]
# 58 Nodes
# body_sent_from_optimizer = [
# {
# "type": "NodeTypeRequirement",
# "nodeTypes": ["IAAS"],
# "jobIdForByon": "dummy-app-id",
# "jobIdForEDGE": "dummy-app-id"
# },
# {
# "type": "AttributeRequirement",
# "requirementClass": "hardware",
# "requirementAttribute": "cores",
# "requirementOperator": "EQ",
# "value": "2"
# },
# {
# "type": "AttributeRequirement",
# "requirementClass": "hardware",
# "requirementAttribute": "ram",
# "requirementOperator": "EQ",
# "value": "4096"
# # "nodeTypes": ["EDGES"]
# "nodeTypes": ["IAAS", "PAAS", "FAAS", "BYON", "EDGE", "SIMULATION"]
# # ,"jobIdForEDGE": "FCRnewLight0"
# }
# # ,{
# # "type": "AttributeRequirement",
# # "requirementClass": "hardware",
# # "requirementAttribute": "ram",
# # "requirementOperator": "EQ",
# # "value": "2"
# # }
# ]
# logging.info(body_sent_from_optimizer)
# print("Extracted body from Optimizer Message:", body_sent_from_optimizer)
print("Extracted body from Optimizer Message:", body_sent_from_optimizer)
## Prepare message to be send to SAL
# Convert the body data to a JSON string
# body_json_string = json.dumps(body_sent_from_optimizer) # For Sender
body_json_string = body_sent_from_optimizer # For Optimizer
# body_json_string = json.dumps(body_sent_from_optimizer)
body_json_string = body_sent_from_optimizer
RequestToSal = { # Dictionary
"metaData": {"user": "admin"}, # key [String "metaData"] value [dictionary]
"body": body_json_string # key [String "body"] value [JSON String]
}
# logging.info("RequestToSal: %s", RequestToSal)
print("RequestToSal:", RequestToSal)
# print("RequestToSal:", RequestToSal)
# print("Is RequestToSal a valid dictionary:", isinstance(RequestToSal, dict))
# print("Is the 'body' string in RequestToSal a valid JSON string:", is_json(RequestToSal["body"]))
@ -112,128 +92,106 @@ class SyncedHandler(Handler):
sal_reply = context.publishers['SAL-GET'].send_sync(RequestToSal)
## Process SAL's Reply
# sal_reply_body = sal_reply.get('body')
sal_body = sal_reply.get('body') # Get the 'body' as a JSON string
# try:
# # Parse the JSON string to a Python object
# nodes_data = json.loads(sal_body)
# total_nodes = len(nodes_data) # Get the total number of nodes
#
# # Check if more than 51 nodes exist
# if total_nodes > 58:
# print("More than 58 nodes exist. Only the first 51 nodes will be processed.")
# # Filter to only include the first 51 nodes
# sal_reply_body = nodes_data[:60]
# else:
# print(f"Total {total_nodes} nodes found. Processing all nodes.")
# sal_reply_body = sal_reply.get('body')
#
# except json.JSONDecodeError as e:
# print(f"Error parsing JSON: {e}")
# filename = 'SAL_Response_10EdgeDevs.json'
# with open(filename, 'r') as file:
# sal_reply_body = json.load(file)
# print("SAL's Reply from JSON File:", sal_reply_body)
try:
# Parse the JSON string to a Python object
nodes_data = json.loads(sal_body)
total_nodes = len(nodes_data) # Get the total number of nodes
# Check if there is any error in SAL's reply body
if 'key' in nodes_data and any(keyword in nodes_data['key'].lower() for keyword in ['error', 'exception']):
print("Error found in message body:", nodes_data['message'])
sal_reply_body = []
else: # No error found in SAL's reply body
total_nodes = len(nodes_data) # Get the total number of nodes
print("Total Nodes in SAL's reply:", total_nodes)
# Check if more than 58 nodes exist
if total_nodes > 400:
print("More than 58 nodes exist. Only the first 51 nodes will be processed.")
# Filter to only include the first 51 nodes and convert back to JSON string
sal_reply_body = json.dumps(nodes_data[:400])
else:
print(f"Total {total_nodes} nodes found. Processing all nodes.")
# Keep sal_reply_body as is since it's already a JSON string
sal_reply_body = sal_body
if total_nodes > 400: # Check if more than 400 nodes received
print("More than 400 nodes returned from SAL.")
# Filter to only include the first 400 nodes and convert back to JSON string
sal_reply_body = json.dumps(nodes_data[:400])
elif total_nodes > 0 and total_nodes <= 400:
print(f"Total {total_nodes} nodes returned from SAL. Processing all nodes.")
# Keep sal_reply_body as is since it's already a JSON string
sal_reply_body = sal_body
else:
print(f"Total {total_nodes} nodes returned from SAL.")
sal_reply_body = []
except json.JSONDecodeError as e:
print(f"Error parsing JSON: {e}")
sal_reply_body = "[]" # Default to an empty JSON array as a string in case of error
print(f"Error parsing JSON reply from SAL: {e}")
sal_reply_body = [] # Default to an empty JSON array as a string in case of error
if sal_reply_body: # Check whether SAL's reply body is empty
# logging.info(f"Whole reply Received from SAL: {sal_reply}")
if sal_reply_body: # Check whether SAL's reply body is empty
# logging.info(f"Reply Received from SAL: {sal_reply}")
# print("SAL reply Body:", sal_reply_body)
# Search for application_id, Read JSON and create data to pass to Evaluation
if check_json_file_exists(application_id_optimizer): # Application JSON exist in DB
print(f"JSON file for application ID {application_id_optimizer} exists.")
node_ids = extract_SAL_node_candidate_data(sal_reply)[2] # 0,1,2nd Position returns the function
# node_ids = ['8a7482868df473cc018df47d8ea60003', '8a7482868df473cc018df47d8fc70005', '8a7482868df473cc018df47d90e70007', '8a7482868df473cc018df47d92090009', '8a7482868df473cc018df47d9326000b', '8a7482868df473cc018df47d9445000d', '8a7482868df473cc018df47d957f000f', '8a7482868df473cc018df47d96a50011', '8a7482868df473cc018df47d97c70013', '8a7482868df473cc018df47d98e30015']
# print("node_ids_SAL:", node_ids_SAL)
# Check if there is any difference in available nodes between saved data in DB and SAL's reply
data_table, relative_wr_data, immediate_wr_data, node_names = read_application_data(application_id_optimizer, node_ids)
if not node_names:
node_names = node_ids
print("data_table filtered from DB:", data_table)
print("node_ids filtered from DB:", node_ids)
print("node_names filtered from DB:", node_names)
# I need to use the most updated data for nodes sent from SAL,
# I can modify the function to retrieve only WR info but there is a problem if other criteria are used
# Maybe I have to use the new data only for the criteria with data coming from SAL and the saved ones for the
# rest criteria
# In case a new node sent from SAL which I have not data saved, then do not consider it if also other crieria
# exist rather than the ones
else: # Application JSON does not exist in DB
print(f"JSON file for application ID {application_id_optimizer} does not exist.")
# Read data from SAL's response by calling the function extract_node_candidate_data()
# extracted_data, number_of_nodes, node_ids, node_names = extract_node_candidate_data('SAL_Response_11EdgeDevs.json')
extracted_data, number_of_nodes, node_ids, node_names = extract_SAL_node_candidate_data(sal_reply_body)
# print("extracted_data:", extracted_data)
print("node_ids:", node_ids)
# Use the create_criteria_mapping() to get the criteria mappings
# selected_criteria = ["Operating cost", "Memory Price", "Number of CPU Cores", "Memory Size", "Storage Capacity"]
selected_criteria = ["Number of CPU Cores", "Memory Size"]
field_mapping = create_criteria_mapping(selected_criteria, extracted_data)
# Create data_table:
data_table = create_data_table(selected_criteria, extracted_data, field_mapping)
relative_wr_data = []
immediate_wr_data = []
print("created_data_table:", data_table)
# Check the number of nodes before Evaluation
print("There are " + str(len(node_ids)) + " elements in node_ids")
if total_nodes > 1:
# Search for application_id, Read JSON and create data to pass to Evaluation
if check_json_file_exists(application_id_optimizer): # Application JSON exist in DB
print(f"JSON file for application ID {application_id_optimizer} exists.")
# Check if there are differences in available nodes between saved data in JSON file and SAL's reply
data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = read_application_data(application_id_optimizer, sal_reply_body)
# print("sal_reply_body:", sal_reply_body)
# print("data_table filtered from JSON and SAL:", data_table)
# print("node_ids filtered from JSON and SAL:", node_ids)
# print("relative_wr_data:", relative_wr_data)
# print("immediate_wr_data:", immediate_wr_data)
# print("node_names filtered from JSON and SAL:", node_names)
## Run evaluation
evaluation_results = perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_names, node_ids)
# print("Evaluation Results:", evaluation_results)
else: # Application does not exist in directory
print(f"JSON file for application ID {application_id_optimizer} does not exist.")
# Read data from SAL's response by calling the function extract_node_candidate_data()
# extracted_data_SAL, node_ids, node_names = extract_node_candidate_data('SAL_Response_11EdgeDevs.json')
extracted_data_SAL, node_ids, node_names = extract_SAL_node_candidate_data(sal_reply_body)
# print("extracted_data_SAL:", extracted_data_SAL)
# print("node_ids:", node_ids)
## Extract and save the results
# ScoresAndRanks = evaluation_results['results']
ScoresAndRanks = evaluation_results.get('results', [])
print("Scores and Ranks:", ScoresAndRanks)
# Use the create_criteria_mapping() to get the criteria mappings
# selected_criteria = ["Operating cost", "Memory Price", "Number of CPU Cores", "Memory Size", "Storage Capacity"]
selected_criteria = ["Number of CPU Cores", "Memory Size"]
field_mapping = create_criteria_mapping()
# Create data_table:
data_table = create_data_table(selected_criteria, extracted_data_SAL, field_mapping)
relative_wr_data = []
immediate_wr_data = []
# print("created_data_table:", data_table)
# Append the Score and Rank of each node to SAL's Response
SAL_and_Scores_Body = append_evaluation_results(sal_reply_body, ScoresAndRanks)
# SAL_and_Scores_Body = append_evaluation_results('SAL_Response_11EdgeDevs.json', ScoresAndRanks)
# print("SAL_and_Scores_Body:", SAL_and_Scores_Body)
# Check the number of nodes before Evaluation
print("There are " + str(len(node_ids)) + " nodes for Evaluation")
## Run evaluation
evaluation_results = perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_names, node_ids)
# print("Evaluation Results:", evaluation_results)
## Extract and save the results
# ScoresAndRanks = evaluation_results['results']
ScoresAndRanks = evaluation_results.get('results', [])
# print("Scores and Ranks:", ScoresAndRanks)
# Append the Score and Rank of each node to SAL's Response
SAL_and_Scores_Body = append_evaluation_results(sal_reply_body, ScoresAndRanks)
# print("SAL_and_Scores_Body:", SAL_and_Scores_Body)
else:
print("There is only one node!")
# Append the Score and Rank of each node to SAL's Response
SAL_and_Scores_Body = append_evaluation_results(sal_reply_body, [])
## Prepare message to be sent to OPTIMIZER
# CFSBResponse = read_dummy_response_data_toOpt('CFSB_Body_Response.json') # Data and Scores for 5 Nodes
CFSBResponse = {
"metaData": {"user": "admin"},
"body": SAL_and_Scores_Body
"metaData": {"user": "admin"},
"body": SAL_and_Scores_Body
}
print("CFSBResponse:", CFSBResponse)
# print("CFSBResponse:", CFSBResponse)
# Writing the formatted JSON to a json file
formatted_json = json.dumps(CFSBResponse, indent=4)
# Writing the formatted JSON to a file named test.json
with open('CFSBResponse.json', 'w') as file:
file.write(formatted_json)
print("Formatted JSON has been saved to CFSBResponse.json")
else: # Then SAL's reply body is empty send an empty body to Optimizer
else: # Then SAL's reply body is empty send an empty body to Optimizer
print("No Body in reply from SAL!")
# Send [] to Optimizer
CFSBResponse = {
@ -248,6 +206,14 @@ class SyncedHandler(Handler):
logging.error(f"Failed to parse message body from Optimizer as JSON: {e}")
def requestSAL(self, RequestToSal):
sal_reply = Context.publishers['SAL-GET'].send_sync(RequestToSal)
# Process SAL's Reply
sal_body = sal_reply.get('body') # Get the 'body' as a JSON string
# print("sal_body requestSAL function:", sal_body)
return sal_body
class Bootstrap(ConnectorHandler):
context = None
def ready(self, context: Context):
@ -279,6 +245,13 @@ def start_exn_connector_in_background():
thread.daemon = True # Daemon threads will shut down immediately when the program exits
thread.start()
def call_publisher(body):
handler = SyncedHandler()
request = handler.requestSAL(body)
return request
# Used to read dummy response and send to Optimizer using JSON
# I have already sent to Optimizer using this function
def read_dummy_response_data_toOpt(file_path):
@ -291,6 +264,7 @@ def read_dummy_response_data_toOpt(file_path):
}
return encapsulated_data
def is_json(myjson):
try:
json_object = json.loads(myjson)

4
cfsb-backend/app.py
View File

@ -1,11 +1,7 @@
from app_factory import create_app
from dotenv import load_dotenv
from activemq import start_exn_connector_in_background
from activemqOLD import start_exn_connector_in_background1
from app_factory import create_app # Import your Flask app factory
load_dotenv()
app = create_app()
# Start the EXN connector in the background
start_exn_connector_in_background()

26
cfsb-backend/docker-compose.yml
View File

@ -1,26 +0,0 @@
version: '3.0'
services:
web:
build:
context: .
dockerfile: Dockerfile
ports:
- "8001:8001"
env_file:
- .env.prod
depends_on:
- db
db:
image: postgres:16
ports:
- "5432:5432"
environment:
- POSTGRES_USER=dbuser
- POSTGRES_PASSWORD=pass123
- POSTGRES_DB=fog_broker
volumes:
- postgres_data:/var/lib/postgresql/data/
- ./db/db_script.sql:/docker-entrypoint-initdb.d/db_script.sql
volumes:
postgres_data:

80
cfsb-backend/edge_data_ipat.json Normal file
View File

@ -0,0 +1,80 @@
{
"_id": "b4ce322c-698a-43b9-a889-bf0da2a4dcb9",
"os": "LINUX",
"name": "Test VM #0001",
"owner": "admin",
"ipAddress": "10.10.0.6",
"location": {
"name": "laptop",
"latitude": 12.345,
"longitude": 56.789
},
"username": "ubuntu",
"password": [
"u",
"b",
"u",
"n",
"t",
"u"
],
"publicKey": [],
"deviceInfo": {
"CPU_SOCKETS": "1",
"CPU_CORES": "10",
"CPU_PROCESSORS": "20",
"RAM_TOTAL_KB": "16218480",
"RAM_AVAILABLE_KB": "13366788",
"RAM_FREE_KB": "10943372",
"RAM_USED_KB": "5275108",
"RAM_UTILIZATION": "32.5253",
"DISK_TOTAL_KB": "1055762868",
"DISK_FREE_KB": "976527612",
"DISK_USED_KB": "79235256",
"DISK_UTILIZATION": "7.50502",
"OS_ARCHITECTURE": "x86_64",
"OS_KERNEL": "Linux",
"OS_KERNEL_RELEASE": "5.15.133.1-microsoft-standard-WSL2"
},
"requestId": "eb6441fc-613a-482e-ba94-b16db57ecd36",
"creationDate": "2024-01-15T13:23:40.602Z",
"lastUpdateDate": "2024-01-15T14:32:43.485Z",
"status": "HEALTHY",
"nodeReference": "40ed1989-49ba-4496-a5c5-3d8ca1a18972",
"messages": [],
"statusUpdate": {
"ipAddress": "10.10.0.6",
"clientId": "VM-LINUX-TEST-VM-0001-Test VM #0001-DEFAULT-10.10.0.6-_",
"state": "REGISTERED",
"stateLastUpdate": "2024-01-15T13:23:47.463Z",
"reference": "40ed1989-49ba-4496-a5c5-3d8ca1a18972",
"errors": []
},
"metrics": {
"ipAddress": "10.10.0.6",
"clientId": "VM-LINUX-TEST-VM-0001-Test VM",
"timestamp": "2024-01-15T14:32:33.467Z",
"metrics": {
"count-total-events-failures": 0,
"count-total-events-text": 0,
"tx": 0,
"count-total-events-other": 0,
"count-event-forwards-success": 0,
"count-event-forwards-failure": 0,
"rx": 0,
"count-total-events": 0,
"cpu": 0.6,
"uptime": 10742,
"count-event-local-publish-failure": 0,
"count-total-events-object": 0,
"disk": 2.48262,
"count-event-local-publish-success": 0,
"updatetime": 1705318391,
"currdatetime": 1705329133,
"ram": 23.7719
},
"latestEvents": []
},
"retries": 0,
"_class": "eu.nebulous.resource.discovery.monitor.model.Device"
}

311
cfsb-backend/routes.py
View File

@ -7,9 +7,11 @@ from data_types import get_attr_data_type
import db.db_functions as db_functions
import os
import time
import get_data as file
import activemq
# from activemq import connector_handler
import traceback
import logging
# logging.disable(logging.CRITICAL)
main_routes = Blueprint('main', __name__)
@ -19,6 +21,74 @@ NoData_Variables = ['attr-security', 'attr-performance-capacity', 'attr-performa
Cont_Variables = ['attr-performance', 'attr-financial', 'attr-performance-capacity-memory',
'attr-performance-capacity-memory-speed']
dummy_node_data = {
"id": "8a7481d98e702b64018e702cbe070000",
"nodeCandidateType": "EDGE",
"jobIdForByon": "",
"jobIdForEdge": "FCRnewLight0",
"price": 0.0,
"cloud": {
"id": "edge",
"endpoint": "",
"cloudType": "EDGE",
"api": "",
"credential": "",
"cloudConfiguration": {
"nodeGroup": "",
"properties": {}
},
"owner": "EDGE",
"state": "",
"diagnostic": ""
},
"location": {
"id": "edge-location-KmVf4xDJKL7acBGc",
"name": "",
"providerId": "",
"locationScope": "",
"isAssignable": "",
"geoLocation": {
"city": "Warsaw",
"country": "Poland",
"latitude": 52.237049,
"longitude": 21.017532
},
"parent": "",
"state": "",
"owner": ""
},
"image": {
"id": "edge-image-KmVf4xDJKL7acBGc",
"name": "edge-image-name-UBUNTU-UNKNOWN",
"providerId": "",
"operatingSystem": {
"operatingSystemFamily": "UBUNTU",
"operatingSystemArchitecture": "UNKNOWN",
"operatingSystemVersion": 1804.00
},
"location": "",
"state": "",
"owner": ""
},
"hardware": {
"id": "edge-hardware-KmVf4xDJKL7acBGc",
"name": "",
"providerId": "",
"cores": 1,
"ram": 1,
"disk": 1.0,
"fpga": 0,
"location": "",
"state": "",
"owner": ""
},
"pricePerInvocation": 0.0,
"memoryPrice": 0.0,
"nodeId": "",
"environment": ""
}
#Used in HomePage.vue to save app_id and user_id
# @main_routes.route('/save_ids', methods=['POST'])
# def save_ids():
@ -34,7 +104,6 @@ Cont_Variables = ['attr-performance', 'attr-financial', 'attr-performance-capaci
#Used in CriteriaSelection.vue
@main_routes.route('/get_hierarchical_category_list')
def get_hierarchical_category_list():
# TODO order by title in every level
items_list = file.get_level_1_items() # Assume this function returns the list correctly
if items_list is not None:
# Return the list as a JSON response
@ -48,101 +117,196 @@ def get_hierarchical_category_list():
def process_selected_criteria():
try:
data = request.json
# Selected Criteria by the User from the List
selected_criteria = data.get('selectedItems', [])
# Extract app_id, user_id
application_id = data.get('app_id') # Take it from local storage from frontend
# application_id = 'd535cf554ea66fbebfc415ac837a5828' #dummy application_id_optimizer
user_id = data.get('user_id') # Take it from local storage from frontend
print("user_id:", user_id)
print("application_id:", application_id)
## Prepare message to be send to SAL
message_for_SAL = [ # User side so ask SAL for every available node
{
"type": "NodeTypeRequirement",
"nodeTypes": ["IAAS", "PAAS", "FAAS", "BYON", "EDGE", "SIMULATION"]
# "jobIdForEDGE": "FCRnewLight0"
}
# application_id = data.get('app_id')
# user_id = data.get('user_id')
# print("user_id:", user_id)
# print("application_id:", application_id)
message_for_SAL = [{
"type": "NodeTypeRequirement",
"nodeTypes": ["IAAS", "PAAS", "FAAS", "BYON", "EDGE", "SIMULATION"]}
# ,{
# "type": "AttributeRequirement",
# "requirementClass": "hardware",
# "requirementAttribute": "cores",
# "requirementOperator": "GEQ",
# "value": "64"
# },
# {
# "type": "AttributeRequirement",
# "requirementClass": "hardware",
# "requirementAttribute": "ram",
# "requirementOperator": "GEQ",
# "value": "33000"
# }
]
# Convert the body data to a JSON string
body_json_string = json.dumps(message_for_SAL)
body_json_string_for_SAL = json.dumps(message_for_SAL)
RequestToSal = { # Dictionary
"metaData": {"user": "admin"}, # key [String "metaData"] value [dictionary]
"body": body_json_string # key [String "body"] value [JSON String]
RequestToSal = {
"metaData": {"user": "admin"},
"body": body_json_string_for_SAL
}
print("RequestToSal:", RequestToSal)
# print("RequestToSal:", RequestToSal)
# print("Is RequestToSal a valid dictionary:", isinstance(RequestToSal, dict))
# print("Is the 'body' string in RequestToSal a valid JSON string:", is_json(RequestToSal["body"]))
sal_reply = activemq.call_publisher(RequestToSal)
nodes_data = json.loads(sal_reply) if isinstance(sal_reply, str) else sal_reply
# print("nodes_data", nodes_data)
## Request the node candidates from SAL
# sal_reply = activemq.context.publishers['SAL-GET'].send_sync(RequestToSal)
extracted_data, node_ids, node_names = extract_SAL_node_candidate_data_Front(nodes_data)
# print("extracted_data:", extracted_data)
field_mapping = create_criteria_mapping()
# print("field_mapping", field_mapping)
## Process SAL's Reply
# extracted_data, number_of_nodes, node_ids, node_names = extract_SAL_node_candidate_data(sal_reply)
# extracted_data, number_of_nodes, node_names = extract_node_candidate_data('dummy_data_node_candidates.json')
extracted_data, number_of_nodes, node_ids, node_names = extract_node_candidate_data('SAL_Response_11EdgeDevs.json')
print("extracted_data:", extracted_data)
default_list_criteria_mapping = {
# "Cost": "price",
"Operating cost": "price",
"Memory Price": "memoryPrice",
"Number of CPU Cores": "cores",
"Memory Size": "ram",
"Storage Capacity": "disk"
}
# Use the create_criteria_mapping() to get the criteria mappings
field_mapping = create_criteria_mapping(selected_criteria, extracted_data)
grid_data = {name: [] for name in node_names}
grid_data = {}
# Prepare the data to be sent to DataGrid.vue
# Blank by default for the Selected Criteria not found in mapping
for node_data in extracted_data:
node_name = node_data.get('name') # Using name to match
node_id = node_data.get('id') # Extract the node ID
grid_data[node_name] = {"id": node_id, "criteria": []}
node_id = node_data.get('id')
# print("Before create_node_name")
node_name = create_node_name(node_data) if node_data else "Unknown"
# print("After create_node_name")
if node_name in grid_data: # Check if node_name exists in grid_data keys
for item in selected_criteria:
criterion_data = {}
criterion_data["data_type"] = get_attr_data_type(item)
item_data_dict = file.get_subject_data(file.SMI_prefix + item)
criterion_data["title"] = item_data_dict["title"]
field_name = field_mapping.get(criterion_data["title"], item)
if node_id and node_id not in grid_data:
grid_data[node_id] = {"name": node_name, "criteria": []}
# Check if the field_name is a direct key or nested inside 'hardware'
if field_name in node_data:
value = node_data[field_name]
elif 'hardware' in node_data and field_name in node_data['hardware']:
value = node_data['hardware'][field_name]
hardware_info = node_data.get('hardware', {}) # contains the values for criteria coming from SAL
for criterion_key in selected_criteria:
# print("criterion_key:", criterion_key)
criterion_info = file.get_subject_data(file.SMI_prefix + criterion_key) # It contains the titles of the criteria
# print("criterion_info:", criterion_info)
# Resolve title and then map title to field name
criterion_data_type = get_attr_data_type(criterion_key) # criterion_data_type: {'type': 1, 'values': ['Low', 'Medium', 'High']}
# print("criterion_data_type:", criterion_data_type)
criterion_title = criterion_info["title"]
# Fetch the values of the selected default criteria
if criterion_title in default_list_criteria_mapping:
SAL_criterion_name = field_mapping.get(criterion_title) # Map the criterion title with the criterion name in SAL's reply
value = hardware_info.get(SAL_criterion_name, "N/A") # Get the criterion values
else:
# Handle other criteria (this part may need adjustment based on your actual data structure)
# value = "N/A" # Placeholder for the logic to determine non-default criteria values
# Generate random or default values for rest criteria
type_value = criterion_data_type['type']
# print("type_value:", type_value)
if type_value == 1:
value = random.choice(["High", "Medium", "Low"])
elif type_value == 5:
value = random.choice(["True", "False"])
else:
# Generate random or default values for unmapped criteria or missing data
item_data_type_value = criterion_data["data_type"].get('type')
if item_data_type_value == 1:
value = random.choice(["High", "Medium", "Low"])
elif item_data_type_value == 5:
value = random.choice(["True", "False"])
else:
value = round(random.uniform(1, 100), 2)
value = round(random.uniform(1, 100), 2)
criterion_data["value"] = value if value != 0 else 0.00001
# grid_data[node_id].append(criterion_data)
# grid_data[node_name].append(criterion_data) # Use node_name as key
grid_data[node_name]["criteria"].append(criterion_data)
criterion_data = {
"title": criterion_title,
"value": value,
"data_type": criterion_data_type # criterion_data_type: {'type': 1, 'values': ['Low', 'Medium', 'High']}
}
grid_data[node_id]["criteria"].append(criterion_data)
# Conversion to list format remains unchanged
# grid_data_with_names = [{'name': name, 'criteria': data} for name, data in grid_data.items()]
grid_data_with_names = [{'name': name, 'id': data["id"], 'criteria': data["criteria"]} for name, data in grid_data.items()]
print("grid_data_with_names:", grid_data_with_names)
grid_data_with_names = [{
'name': data["name"],
'id': node_id,
'criteria': data["criteria"]
} for node_id, data in grid_data.items()]
# print("grid_data_with_names:", grid_data_with_names)
# Send the comprehensive grid_data_with_names to the frontend
return jsonify({
'success': True,
'gridData': grid_data_with_names,
'NodeNames': node_names
})
except Exception as e:
print(f"Error processing selected items: {e}")
traceback.print_exc()
return jsonify({'success': False, 'error': str(e)}), 500
# Used in WR.vue
# Works by reading a JSON file with dummy data
# def process_selected_criteria():
# try:
# data = request.json
# # Selected Criteria by the User from the List
# selected_criteria = data.get('selectedItems', [])
# # Extract app_id, user_id
# application_id = data.get('app_id') # Take it from local storage from frontend
# # application_id = 'd535cf554ea66fbebfc415ac837a5828' #dummy application_id_optimizer
# user_id = data.get('user_id') # Take it from local storage from frontend
# print("user_id:", user_id)
# print("application_id:", application_id)
#
# ## Process SAL's Reply
# # extracted_data, number_of_nodes, node_names = extract_node_candidate_data('dummy_data_node_candidates.json')
# extracted_data, node_ids, node_names = extract_node_candidate_data('SAL_Response_11EdgeDevs.json')
# print("extracted_data:", extracted_data)
#
# # Use the create_criteria_mapping() to get the criteria mappings
# field_mapping = create_criteria_mapping(selected_criteria, extracted_data)
# grid_data = {name: [] for name in node_names}
#
# # Prepare the data to be sent to DataGrid.vue
# for node_data in extracted_data:
# node_name = node_data.get('name') # Using name to match
# node_id = node_data.get('id') # Extract the node ID
# grid_data[node_name] = {"id": node_id, "criteria": []}
#
# if node_name in grid_data: # Check if node_name exists in grid_data keys
# for item in selected_criteria:
# criterion_data = {}
# criterion_data["data_type"] = get_attr_data_type(item)
# item_data_dict = file.get_subject_data(file.SMI_prefix + item)
# criterion_data["title"] = item_data_dict["title"]
# field_name = field_mapping.get(criterion_data["title"], item)
#
# # Check if the field_name is a direct key or nested inside 'hardware'
# if field_name in node_data:
# value = node_data[field_name]
# elif 'hardware' in node_data and field_name in node_data['hardware']:
# value = node_data['hardware'][field_name]
# else:
# # Generate random or default values for unmapped criteria or missing data
# item_data_type_value = criterion_data["data_type"].get('type')
# if item_data_type_value == 1:
# value = random.choice(["High", "Medium", "Low"])
# elif item_data_type_value == 5:
# value = random.choice(["True", "False"])
# else:
# value = round(random.uniform(1, 100), 2)
#
# criterion_data["value"] = value if value != 0 else 0.00001
# # grid_data[node_id].append(criterion_data)
# grid_data[node_name]["criteria"].append(criterion_data)
#
# # Conversion to list format remains unchanged
# # grid_data_with_names = [{'name': name, 'criteria': data} for name, data in grid_data.items()]
# grid_data_with_names = [{'name': name, 'id': data["id"], 'criteria': data["criteria"]} for name, data in grid_data.items()]
# print("grid_data_with_names:", grid_data_with_names)
#
# # Send the comprehensive grid_data_with_names to the frontend
# return jsonify({
# 'success': True,
# 'gridData': grid_data_with_names,
# 'NodeNames': node_names
# })
# except Exception as e:
# print(f"Error processing selected items: {e}")
# traceback.print_exc()
# return jsonify({'success': False, 'error': str(e)}), 500
@main_routes.route('/process-evaluation-data', methods=['POST'])
def process_evaluation_data():
try:
@ -150,14 +314,15 @@ def process_evaluation_data():
if data is None:
raise ValueError("Received data is not in JSON format or 'Content-Type' header is not set to 'application/json'")
print("JSON data:", data)
# print("JSON in process_evaluation_data:", data)
# Transform grid data to table and get node names directly from the function
data_table, relative_wr_data, immediate_wr_data, node_names, node_ids = transform_grid_data_to_table(data)
# print("data_table:", data_table)
# print("data_table FRONT:", data_table)
# print("relative_wr_data:", relative_wr_data)
# print("immediate_wr_data:", immediate_wr_data)
# print("node_names:", node_names)
# print("# node_names:", len(node_names))
# print("# node_ids:", len(node_ids))
# Run Optimization - Perform evaluation
results = perform_evaluation(data_table, relative_wr_data, immediate_wr_data, node_names, node_ids)

140
cfsb-backend/test.py Normal file
View File

@ -0,0 +1,140 @@
# ActiveMQ communication logic via EXN library
import sys
import threading
import json
import time
sys.path.insert(0,'../exn')
import logging
from dotenv import load_dotenv
load_dotenv()
from proton import Message
from exn import core
from exn.connector import EXN
from exn.core.consumer import Consumer
from exn.core.synced_publisher import SyncedPublisher
from exn.core.publisher import Publisher
from exn.core.context import Context
from exn.core.handler import Handler
from exn.handler.connector_handler import ConnectorHandler
from User_Functions import *
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logging.getLogger('exn.connector').setLevel(logging.DEBUG)
class SyncedHandler(Handler):
def on_message(self, key, address, body, message: Message, context=None):
logging.info(f"[SyncedHandler] Received {key} => {address}: {body}")
logging.info("on_message in SyncedHandler is executed")
logging.info(f"[body] {body}")
# Triggered by OPTIMIZER, Get app id, correlation id and filters
# if address == "topic://eu.nebulouscloud.cfsb.get_node_candidates":
if key == "OPT-triggering":
logging.info("Entered in OPT-triggering Key")
# Save the correlation_id (We do not have it from the app_side)
# Optimizer_correlation_id = '88334290cad34ad9b21eb468a9f8ff11' # dummy correlation_id
Optimizer_correlation_id = message.correlation_id
logging.info(f"Optimizer_correlation_id {message.correlation_id}")
application_id = message.subject # can be taken also from message.annotations.application
try:
opt_message_data = body
print("Message from Optimizer:", opt_message_data)
# Extract 'body' from opt_message_data
# opt_body_data = opt_message_data.get('body', {})
opt_body_data =[
{
"type": "NodeTypeRequirement",
"nodeTypes": ["EDGE"],
"jobIdForEDGE": "FCRnewLight0"
}
]
logging.info(opt_body_data)
print("Extracted body from Optim Message:", opt_body_data)
## Prepare message to be send to SAL
RequestToSal = {
"metaData": {"user": "admin"},
"body": opt_body_data
}
print("RequestToSal:", RequestToSal)
# Convert the Python structure to a JSON string
# RequestToSal = json.dumps(RequestToSal)
# Request the node candidates from SAL
sal_reply = context.publishers['SAL-GET'].send_sync(RequestToSal, application_id,
properties={'correlation_id': Optimizer_correlation_id}, raw=False)
# sal_reply = context.publishers['SAL-GET'].send_sync(RequestToSal, application_id)
if sal_reply:
logging.info(f"Received reply from SAL: {sal_reply}")
print("SAL reply:", sal_reply)
else:
print("No reply from SAL!")
## Prepare message to be sent to OPTIMIZER
CFSBResponse = read_dummy_response_data_toOpt('CFSB_Body_Response.json')
# SAL_and_Scores_Body = Give me a short example
# Encapsulate the data within the "body" structure
# CFSBResponse = {
# "metaData": {"user": "admin"},
# "body": SAL_and_Scores_Body
# }
# print("CFSBResponse:", CFSBResponse)
# Send message to Optimizer
context.get_publisher('SendToOPT').send(CFSBResponse, application_id)
# context.publishers['SendToOPT'].send(CFSBResponse, application_id, properties={
# 'correlation_id': Optimizer_correlation_id}, raw=True)
except json.JSONDecodeError as e:
logging.error(f"Failed to parse message body from Optimizer as JSON: {e}")
class Bootstrap(ConnectorHandler):
context = None
def ready(self, context: Context):
self.context = context
def start_exn_connector_in_background():
def run_connector():
# eu.nebulouscloud.exn.sal.nodecandidate.*
addressSAL_GET = 'eu.nebulouscloud.exn.sal.nodecandidate.get'
addressSAL_GET_REPLY = 'eu.nebulouscloud.exn.sal.nodecandidate.get.reply'
addressOPTtriggering = 'eu.nebulouscloud.cfsb.get_node_candidates'
addressSendToOPT = 'eu.nebulouscloud.cfsb.get_node_candidates.reply'
connector = EXN('ui', url="localhost", port=5672, username="admin", password="admin",
handler=Bootstrap(),
publishers=[
SyncedPublisher('SAL-GET', addressSAL_GET, True, True),
core.publisher.Publisher('SendToOPT', addressSendToOPT, True, True)
],
consumers=[
# Consumer('SAL-GET-REPLY', addressSAL_GET, handler=SyncedHandler(), topic=True, fqdn=True),
Consumer('OPT-triggering', addressOPTtriggering, handler=SyncedHandler(), topic=True, fqdn=True)
])
connector.start()
# Start the EXN connector in a separate thread
thread = threading.Thread(target=run_connector)
thread.daemon = True # Daemon threads will shut down immediately when the program exits
thread.start()
# Used to read dummy JSON and send to Optimizer
def read_dummy_response_data_toOpt(file_path):
with open(file_path, 'r') as file:
data = json.load(file)
# Encapsulating the data within the "body" structure
encapsulated_data = {
"metaData": {"user": "admin"},
"body": data
}
return encapsulated_data

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cfsb-frontend/.env Normal file
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@ -0,0 +1,2 @@
VUE_APP_BACKEND_URL=http://127.0.0.1:5000
VITE_BACKEND_URL=http://127.0.0.1:5000

2
cfsb-frontend/.env.development Normal file
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@ -0,0 +1,2 @@
VUE_APP_BACKEND_URL=http://127.0.0.1:8001
VITE_BACKEND_URL=http://127.0.0.1:8001

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cfsb-frontend/.env.production Normal file
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@ -0,0 +1,2 @@
VUE_APP_BACKEND_URL=http://127.0.0.1:8001
VITE_BACKEND_URL=http://127.0.0.1:8001

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cfsb-frontend/Dockerfile Normal file
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@ -0,0 +1,22 @@
# Step 1: Build Stage
FROM node:16 as build-stage
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm install
COPY . .
RUN npm run build
# Step 2: Nginx Stage
FROM docker.io/nginx:alpine
COPY --from=build-stage /app/dist /usr/share/nginx/html
COPY .env.production /usr/share/nginx/html/.env
EXPOSE 80
CMD ["nginx", "-g", "daemon off;"]

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cfsb-frontend/package.json
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@ -10,6 +10,7 @@
},
"dependencies": {
"chart.js": "^4.4.1",
"package.json": "^2.0.1",
"vue-router": "^4.0.13"
},
"devDependencies": {

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131
cfsb-frontend/src/App.vue
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@ -28,17 +28,55 @@
<!-- Main content where routed components will be displayed -->
<!-- <router-view></router-view>
<button v-if="showCriteriaSelectionButton" @click="goToCriteriaSelection">Go to Criteria Selection</button> -->
<div class="modal fade" id="userLoginModal" aria-hidden="false">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<h1 class="modal-title">User login</h1>
<button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
</div>
<div class="modal-body">
<form @submit.prevent="submitUserLoginForm">
<div class="mb-3">
<label for="app_id" class="form-label">Insert Application ID</label>
<input type="text" class="form-control" id="app_id" v-model="app_id" placeholder="Application ID" required>
</div>
<div class="mb-3">
<label for="username" class="form-label">Your username</label>
<input type="text" class="form-control" id="username" v-model="username" placeholder="Username" required>
</div>
<div class="mb-3">
<label for="password" class="form-label">Your password</label>
<input type="password" class="form-control" id="password" v-model="password" placeholder="Password" required>
</div>
<button type="submit" class="btn btn-success">Login</button>
</form>
<div v-if="!login" class="alert alert-danger">Error</div>
</div>
<div class="modal-footer">
<button type="button" class="btn btn-secondary" data-bs-dismiss="modal" ref="modalCloseBtn">Close</button>
</div>
</div>
</div>
</div>
<footer class="footer text-center p-2">
<span class="text-white">&copy NebulOus</span>
<span class="text-white">&copy NebulOus - Cloud Fog Service Broker</span>
</footer>
</div>
</template>
<style>
:root {
--main-color: #7030A0;
--main-color: #1b253b;
--secondary-color: #e0cffc;
--color-indigo-700: #3d0a91;
--color-indigo-700: #172135;
--light-gray-color: #f8f9fa;
--medium-gray-color: #6c757d;
}
@ -89,22 +127,107 @@
.footer {
background-color: var(--main-color);
margin-top: 15px;
}
</style>
<script>
export const backendURL = import.meta.env.VITE_BACKEND_URL;
const apiURL = backendURL;
export default {
name: 'App',
data() {
return {
username: "",
password: "",
uuid: "",
app_id: "",
login: true
}
},
methods: {
goToCriteriaSelection() {
this.$router.push('/criteria-selection');
}
},
checkUserLogin() {
let uuid = localStorage.getItem('fog_broker_user_uuid');
if (uuid) {
console.log("user is set");
} else {
console.log("user not set");
let myModal = new bootstrap.Modal(document.getElementById('userLoginModal'));
myModal.show();
}
},
async submitUserLoginForm() {
console.log('username = :', this.username);
let user_data = {
'username': this.username,
'password': this.password,
'app_id': this.app_id,
}
let result = await this.fetchUser(user_data)
this.username = "";
this.password = "";
},
async fetchUser(user_data) {
try {
const response = await fetch(apiURL+'/login', {
method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify(user_data)
});
const data = await response.json();
console.log(data);
if (data.length===1) {
this.uuid = data[0][2];
console.log(data[0][2]);
localStorage.setItem('fog_broker_user_uuid', data[0][2]);
localStorage.setItem('fog_broker_app_id', user_data.app_id);
let elem = this.$refs.modalCloseBtn
elem.click()
this.login = true;
} else {
this.login = false;
}
} catch (error) {
console.error('Error fetching user:', error);
}
},
getURLparams() {
let app_in_url = false
let user_in_url = false
let app_id_from_js = new URL(location.href).searchParams.get('app_id');
let user_id_from_js = new URL(location.href).searchParams.get('user_id');
if (app_id_from_js) {
console.log('app_id from URL:', app_id_from_js);
this.app_id = app_id_from_js;
app_in_url = true;
localStorage.setItem('fog_broker_app_id', this.app_id);
}
if (user_id_from_js) {
console.log('user_id from URL:', user_id_from_js);
this.uuid = user_id_from_js;
user_in_url = true
localStorage.setItem('fog_broker_user_uuid', this.uuid);
}
if (app_in_url && user_in_url){
return true
} else {
return false
}
},
},
computed: {
showCriteriaSelectionButton() {
return this.$route.path === '/'; /* other conditions */
}
},
mounted() {
this.getURLparams();
this.checkUserLogin();
}
};
</script>

6
cfsb-frontend/src/assets/base.css
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@ -1,8 +1,8 @@
/* color palette from <https://github.com/vuejs/theme> */
:root {
--vt-c-white: #ffffff;
--vt-c-white-soft: #f8f8f8;
--vt-c-white-mute: #f2f2f2;
--vt-c-white: #1B253BFF;
--vt-c-white-soft: #1b253b;
--vt-c-white-mute: #1b253b;
--vt-c-black: #181818;
--vt-c-black-soft: #222222;

63
cfsb-frontend/src/components/CriteriaSelection.vue
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@ -1,28 +1,33 @@
<template>
<div class="row" style="padding-bottom: 2rem">
</div>
<div class="row" style="padding-bottom: 2rem"></div>
<div class="container">
<div class="row justify-content-center">
<div class="col col-12 col-lg-8">
<div class="card">
<div class="card-header">
<!-- Use a flex container for the header -->
<div class="card-header d-flex justify-content-between align-items-center">
<h2>Selection of Criteria</h2>
<!-- Clickable icon and text for expanding/collapsing -->
<span class="expand-collapse-link" @click="toggleExpandAll">
<i v-bind:class="expandIconClass"></i>{{ expandButtonText }}</span>
</div>
<div class="card-body">
<HierarchicalCategoryList
:items="hierarchicalCategoryList"
@selected-items="updateSelectedItems"
></HierarchicalCategoryList>
<p class="description">
Please select at least two criteria to proceed.
</p>
<!-- HierarchicalCategoryList is included here with the necessary bindings -->
<HierarchicalCategoryList ref="hierarchicalList" :items="hierarchicalCategoryList" @selected-items="updateSelectedItems"/>
</div>
</div>
<!-- <div>Selected Items Length: {{ selectedItems.length }}</div>
<button v-if="selectedItems.length > 0" @click="navigateToDataGrid">Go to DataGrid</button> -->
</div>
</div>
</div>
</template>
<script>
export const backendURL = import.meta.env.VITE_BACKEND_URL;
const apiURL = backendURL;
import HierarchicalCategoryList from "@/components/HierarchicalCategoryList.vue";
export default {
@ -33,32 +38,62 @@ export default {
return {
hierarchicalCategoryList: [],
selectedItems: [],
allCategoriesExpanded: false
};
},
mounted() {
console.log('CriteriaSelection.vue mounted');
this.fetchHierarchicalCategoryList();
},
computed: {
expandButtonText() {
return this.allCategoriesExpanded ? 'Collapse All' : 'Expand All';
},
expandIconClass() {
return this.allCategoriesExpanded ? 'bi-arrow-bar-up' : 'bi-arrow-bar-down';
}
},
methods: {
async fetchHierarchicalCategoryList() {
try {
const response = await fetch('http://127.0.0.1:5000/get_hierarchical_category_list');
const response = await fetch(apiURL+'/get_hierarchical_category_list');
const data = await response.json();
this.hierarchicalCategoryList = data;
} catch (error) {
console.error('Error fetching hierarchical category list:', error);
}
},
navigateToDataGrid() {
console.log('Navigating to DataGrid');
this.$router.push({ name: 'DataGrid' });
toggleExpandAll() {
this.allCategoriesExpanded = !this.allCategoriesExpanded;
if (this.$refs.hierarchicalList) {
this.$refs.hierarchicalList.setChildrenVisibility(this.hierarchicalCategoryList, this.allCategoriesExpanded);
}
},
updateSelectedItems(newSelectedItems) {
//console.log('Updating selected items in CriteriaSelection.vue:', newSelectedItems);
this.selectedItems = newSelectedItems;
},
}
},
};
</script>
<style>
.card-header {
display: flex;
justify-content: space-between;
align-items: center;
}
.expand-collapse-link {
cursor: pointer;
color: var(--color-indigo-700); user-select: none;
display: flex;
align-items: center; /* Aligns the icon and text vertically */
}
.expand-collapse-link i {
margin-right: 0.5rem; /* Add some space between the icon and text */
}
</style>

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cfsb-frontend/src/components/DataGrid.vue
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@ -1,25 +1,68 @@
<template>
<div>
<div class="p-4">
<h2>Edge / Fog Nodes Data</h2>
<h2>Nodes Data</h2>
</div>
<!-- <table v-if="gridData.length" class="grid-cell-class">-->
<!-- <thead>-->
<!-- <tr>-->
<!-- <th>Node</th>-->
<!-- &lt;!&ndash; Assuming all entries have the same criteria, using the first one to generate headers &ndash;&gt;-->
<!-- <th v-for="(criterion, index) in gridData[0].criteria" :key="index">-->
<!-- {{ criterion.title }}-->
<!-- </th>-->
<!-- </tr>-->
<!-- </thead>-->
<!-- <tbody>-->
<!-- <tr v-for="(entry, entryIndex) in gridData" :key="entry.name">-->
<!-- <td>{{ entry.name }}</td>-->
<!-- <td v-for="(dataValue, dataIndex) in entry.data_values" :key="`${entry.name}-${dataIndex}`">-->
<!-- &lt;!&ndash; Numeric data type &ndash;&gt;-->
<!-- <template v-if="dataValue.data_type.type === 2">-->
<!-- <input type="number" v-model="dataValue.value" @blur="validateNumeric(entry.data_values, dataIndex)" step="0.5"/>-->
<!-- </template>-->
<table v-if="Object.keys(gridData).length" class="grid-cell-class">
<!-- &lt;!&ndash; Ordinal data type &ndash;&gt;-->
<!-- <template v-else-if="dataValue.data_type.type === 1">-->
<!-- <select v-model="dataValue.value">-->
<!-- <option v-for="option in dataValue.data_type.values" :value="option" :key="option">{{ option }}</option>-->
<!-- </select>-->
<!-- </template>-->
<!-- &lt;!&ndash; Boolean data type &ndash;&gt;-->
<!-- <template v-else-if="dataValue.data_type.type === 5">-->
<!-- <select v-model="dataValue.value">-->
<!-- <option v-for="option in ['True', 'False']" :value="option" :key="option">{{ option }}</option>-->
<!-- </select>-->
<!-- </template>-->
<!-- &lt;!&ndash; Fallback or other data types &ndash;&gt;-->
<!-- <template v-else>-->
<!-- <input type="text" v-model="dataValue.value" />-->
<!-- </template>-->
<!-- </td>-->
<!-- </tr>-->
<!-- </tbody>-->
<!-- </table>-->
<table v-if="gridData.length" class="grid-cell-class">
<thead>
<tr>
<th>Edge / Fog Nodes</th>
<th v-for="(values, column) in gridData" :key="column">{{ values.title }}</th>
<th>Node</th>
<th v-for="(criterion, index) in gridData[0].criteria" :key="index">{{ criterion.title }}</th>
</tr>
</thead>
<tbody>
<tr v-for="index in rowCount" :key="index">
<!-- (-1) Because there is a different indexing in the gridData and the fog node titles that starts from 0 -->
<td>{{ fogNodesTitles[index-1] }}</td>
<td v-for="(values, column) in gridData" :key="`${column}-${index}`">
<select v-if="Ordinal_Variables.includes(column)" v-model="values.data_values[index - 1]">
<option v-for="option in dropdownOptions" :value="option" :key="option">{{ option }}</option>
<tr v-for="(entry, entryIndex) in gridData" :key="entry.name">
<td>{{ entry.name }}</td>
<td v-for="(criterion, criterionIndex) in entry.criteria" :key="`${entry.name}-${criterionIndex}`">
<input v-if="criterion.data_type.type === 2" type="number" v-model="criterion.value" />
<select v-else-if="criterion.data_type.type === 1" v-model="criterion.value">
<option v-for="option in criterion.data_type.values" :value="option" :key="option">{{ option }}</option>
</select>
<input v-else type="text" v-model="values.data_values[index - 1]" />
<select v-else-if="criterion.data_type.type === 5" v-model="criterion.value">
<option v-for="option in ['True', 'False']" :value="option">{{ option }}</option>
</select>
<input v-else type="text" v-model="criterion.value" />
</td>
</tr>
</tbody>
@ -28,58 +71,62 @@
No data to display.
</div>
<div class="pt-4"></div>
<!-- <button @click="SaveDataforEvaluation" class="bg-color-primary">Save and Run Evaluation</button> -->
<button @click="goBackToCriteriaSelection" class="bg-color-primary">Back to Criteria Selection</button>
<button @click="SaveDataforWR" class="bg-color-primary">Save and Add Weight Restrictions</button>
</div>
</template>
<script>
import { useRouter } from 'vue-router';
export const backendURL = import.meta.env.VITE_BACKEND_URL;
const apiURL = backendURL;
export default {
data() {
return {
fogNodesTitles: [],
gridData: [], // Data for the grid
selectedItemsFromBack: [],
Ordinal_Variables: ['attr-reputation', 'attr-assurance', 'attr-security'],
dropdownOptions: ['High', 'Medium', 'Low'], // Options for the dropdown
};
},
setup() {
const router = useRouter();
return {
router
NodeNames: [],
gridData: [], // Updated to be an array to match the structure provided by the backend
};
},
mounted() {
const selectedItems = this.$route.params.selectedItems || [];
if (selectedItems.length > 0) {
this.fetchGridData(selectedItems);
let selectedItemsWithTypes = this.getSelectedItemsFromStorage();
if (!selectedItemsWithTypes.length) {
selectedItemsWithTypes = this.$route.params.selectedItems || [];
}
this.fetchFogNodesTitles();
},
computed: {
rowCount() {
// Check if gridData has any keys and use the first key to find the row count
const firstKey = Object.keys(this.gridData)[0];
return firstKey ? this.gridData[firstKey].data_values.length : 0;
if (selectedItemsWithTypes.length > 0) {
this.fetchGridData(selectedItemsWithTypes.map(item => item.name));
}
},
methods: {
// Receives the Grid Data 1st time
getSelectedItemsFromStorage() {
const storedItems = localStorage.getItem('selectedCriteria');
return storedItems ? JSON.parse(storedItems) : [];
},
async fetchGridData(selectedItems) {
try {
const response = await fetch('http://127.0.0.1:5000/process_selected_items', {
// Retrieve app_id and user_id from local storage directly within this method
const app_id = localStorage.getItem('fog_broker_app_id');
const user_id = localStorage.getItem('fog_broker_user_uuid');
const response = await fetch(apiURL+'/process_selected_criteria', {
method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify({selectedItems}),
// body: JSON.stringify({selectedItems}),
body: JSON.stringify({
selectedItems,
app_id, // Include app_id from local storage
user_id // Include user_id from local storage
})
});
if (response.ok) {
const criteria_data = await response.json();
this.gridData = criteria_data.gridData; // Assigning the gridData from the response
console.log('DataGrid.vue received the criteria data from the Backend:', this.gridData); // Log the received grid data
const { gridData, NodeNames } = await response.json();
// Initialize data_values for each entry in gridData
this.gridData = gridData.map(entry => ({
...entry,
data_values: entry.criteria.map(criterion => ({
value: criterion.value,
data_type: criterion.data_type
}))
}));
this.NodeNames = NodeNames || [];
} else {
throw new Error('Failed to fetch grid data');
}
@ -87,81 +134,136 @@ export default {
console.error('Error fetching grid data:', error);
}
},
fetchFogNodesTitles() { // Receives the names of fog nodes (grid's 1st column)
fetch('http://127.0.0.1:5000/get-fog-nodes-titles')
.then(response => response.json())
.then(data => {
// 'data' is an array like ['Fog Node 1', 'Fog Node 2', ...]
this.fogNodesTitles = data;
})
.catch(error => console.error('Error fetching fog nodes titles:', error));
validateNumeric(entry, criterionIndex) {
// Directly modify and validate numeric value within the entry's criteria
const numericValue = parseFloat(entry.criteria[criterionIndex].value);
if (isNaN(numericValue) || numericValue <= 0) {
alert('Please enter a number greater than zero.');
entry.criteria[criterionIndex].value = ''; // Reset invalid value
return false; // Halt further processing
} else {
entry.criteria[criterionIndex].value = numericValue; // Update with valid numeric value
}
},
validateGridData() {
for (const key in this.gridData) {
if (this.gridData.hasOwnProperty(key)) {
const dataValues = this.gridData[key].data_values;
for (const value of dataValues) {
if (value === 0 || value === null || value === '') {
return false; // Invalid data found
}
for (const entry of this.gridData) {
for (const criterion of entry.criteria) {
// Convert value to string to handle trimming and empty checks
const valueAsString = String(criterion.value).trim();
switch (criterion.data_type.type) {
case 2: // Numeric
const numericValue = parseFloat(valueAsString);
if (isNaN(numericValue) || numericValue <= 0) {
alert('Please enter a valid number for all numeric fields.');
return false; // Prevent further processing
}
break;
case 1: // Ordinal
if (!criterion.data_type.values.includes(criterion.value)) {
alert(`Please select a valid option for ${criterion.title}.`);
return false; // Prevent further processing
}
break;
case 5: // Boolean
if (!["True", "False"].includes(valueAsString)) {
alert(`Please select a valid boolean value for ${criterion.title}.`);
return false; // Prevent further processing
}
break;
default:
// Check for empty values for any other data types
if (valueAsString === '') {
alert(`Please ensure all fields are filled for ${criterion.title}.`);
return false; // Prevent further processing
}
}
}
}
return true; // All data is valid
return true; // All validations passed
},
async SaveDataforWR() {
if (!this.validateGridData()) {
alert('Invalid input: Zero or null values are not accepted.');
return; // Stop submission if validation fails
}
else{
try {
const DataforWR = JSON.stringify({
gridData: this.gridData
});
// Navigate to WR component with data
this.router.push({ name: 'WR', params: { data: DataforWR } });
} catch (error) {
console.error('Error:', error);
}
}
goBackToCriteriaSelection() {
this.$router.push({ name: 'CriteriaSelection' });
},
async SaveDataforEvaluation() {
async SaveDataforWR() {
if (!this.validateGridData()) {
return;
}
// Log the current state of gridData
console.log("Before saving, gridData is:", JSON.parse(JSON.stringify(this.gridData)));
try {
const formattedGridData = this.gridData.map(node => ({
name: node.name,
id: node.id,
criteria: node.criteria.map(criterion => ({
title: criterion.title,
value: criterion.value,
data_type: criterion.data_type.type
}))
}));
const DataforWR = JSON.stringify(formattedGridData);
localStorage.setItem('gridData', DataforWR); // Save gridData to localStorage
// console.log("Save DataforWR DataGrid.VUE to localstorage:", JSON.stringify(JSON.parse(DataforWR), null, 2));
// Save the NodeNames to localStorage
const NodeNames = JSON.stringify(this.NodeNames);
localStorage.setItem('NodeNames', NodeNames);
// Navigate to WR component with prepared data and NodeNames
this.$router.push({
name: 'WR',
params: {
data: DataforWR,
NodeNames: NodeNames // Include NodeNames in the route parameters
}
});
} catch (error) {
console.error('Error:', error);
}
}
}
};
</script>
<style>
/* Basic table styling */
table {
width: 100%;
border-collapse: collapse;
width: 100%;
border-collapse: collapse;
}
/* Header styling */
th {
background-color: #813F8F; /* Primary color */
color: #FFFFFF; /* White text */
padding: 10px;
text-align: center;
background-color: #232d45; /* Primary color */
color: #FFFFFF; /* White text */
padding: 10px;
text-align: center;
}
/* Row styling */
td {
background-color: #E7E7E7; /* Light grey */
color: #374591; /* Secondary color */
padding: 8px;
background-color: #E7E7E7; /* Light grey */
color: #172135; /* Secondary color */
padding: 8px;
font-weight: bold;
}
/* Alternate row colors for better readability */
tr:nth-child(even) {
background-color: #E4DCD5; /* Light tan */
background-color: #155e75; /* Light tan */
}
/* Hover effect on rows */
tr:hover {
background-color: #6FBFFF; /* Light blue */
background-color: #6FBFFF; /* Light blue */
}
/* Additional styles for editable input fields in the table */
@ -200,10 +302,11 @@ button:hover {
select {
width: 100%;
padding: 8px;
border: 1px solid #ccc;
border: 1px solid #1b253b;
}
.grid-cell-class {
text-align: center;
}
</style>
</style>

129
cfsb-frontend/src/components/HierarchicalCategoryList.vue
View File

@ -3,35 +3,37 @@
<form v-if="!isChild" @submit.prevent="submitSelection">
<ul class="list-group">
<li v-for="item in items" :key="item.name" class="list-group-item criteria-card">
<span v-if="item.children.length > 0" @click="toggleCategory(item)" class="float-end" v-bind:title="'Expand ' + item.title"><i class="bi bi-arrow-bar-down" v-bind:aria-label="'Expand ' + item.title"></i></span>
<span v-if="item.children.length > 0" @click="toggleCategory(item)" class="float-end" v-bind:title="'Expand ' + item.title">
<i class="bi bi-arrow-bar-down" v-bind:aria-label="'Expand ' + item.title"></i>
</span>
<label>
<!--
<input v-model="item.checked" type="checkbox" @change="handleCheckboxChange(item)" />
<span @click="toggleCategory(item)" v-bind:title="item.description">{{ item.title }}</span> -->
<!-- <input v-model="item.checked" type="checkbox" @change="handleCheckboxChange(item)" /> -->
<input type="checkbox" :checked="item.checked" @change="() => handleCheckboxChange(item)" />
<span @click="toggleCategory(item)">{{ item.title }}</span>
<span @click="toggleCategory(item)" v-bind:title="item.description"> {{ item.title }} ({{ getTypeName(item.type) }}) </span>
</label>
<ul v-show="item.showChildren" class="list-group">
<!-- Recursive call without Submit button -->
<HierarchicalCategoryList :isChild="true" :items="item.children" @selected-items="updateSelectedItems" />
<!-- <HierarchicalCategoryList :isChild="true" :items="item.children" @selected-items="updateSelectedItems" /> -->
<HierarchicalCategoryList :isChild="true" :items="item.children" />
</ul>
</li>
</ul>
<button @click="goBackToHome" class="bg-color-primary">Back</button>
<!-- Submit button outside the recursive structure -->
<button type="submit" class="bg-color-primary">Submit</button>
<button type="submit" class="bg-color-primary">Next</button>
</form>
<div v-else>
<li v-for="item in items" :key="item.name" class="list-group-item criteria-card">
<span v-if="item.children.length > 0" @click="toggleCategory(item)" class="float-end" v-bind:title="'Expand ' + item.title"><i class="bi bi-arrow-bar-down" v-bind:aria-label="'Expand ' + item.title"></i></span>
<label>
<!-- <input v-model="item.checked" type="checkbox" @change="handleCheckboxChange(item)" />
<span @click="toggleCategory(item)" v-bind:title="item.description">{{ item.title }}</span> -->
<!-- <input v-model="item.checked" type="checkbox" @change="handleCheckboxChange(item)" />-->
<input type="checkbox" :checked="item.checked" @change="() => handleCheckboxChange(item)" />
<span @click="toggleCategory(item)">{{ item.title }}</span>
</label>
<ul v-show="item.showChildren">
<!-- Recursive call without Submit button -->
<HierarchicalCategoryList :isChild="true" :items="item.children" @selected-items="updateSelectedItems" />
<span @click="toggleCategory(item)" v-bind:title="item.description"> {{ item.title }} ({{ getTypeName(item.type) }}) </span>
</label>
<ul v-show="item.showChildren">
<!-- Recursive call without Submit button
<HierarchicalCategoryList :isChild="true" :items="item.children" @selected-items="updateSelectedItems" /> -->
<HierarchicalCategoryList :isChild="true" :items="item.children" />
</ul>
</li>
</div>
@ -46,11 +48,12 @@ export default {
type: Boolean,
default: false,
},
updateItemType: Function,
},
data() {
return {
localSelectedItems: [],
selectedItemsFromBack: [],
};
},
computed: {
@ -95,50 +98,91 @@ export default {
}
return null;
},
setChildrenVisibility(items, visible) {
items.forEach(item => {
item.showChildren = visible;
if (item.children && item.children.length > 0) {
this.setChildrenVisibility(item.children, visible);
}
});
},
updateSelectedItems() {
// Update the selected items list
this.localSelectedItems = this.collectSelectedItems(this.items);
// Emit the updated list
this.$emit('selected-items', this.localSelectedItems);
// Update the selected items list with additional type information
const selectedItemsWithType = this.items
.filter(item => item.checked)
.map(item => ({ name: item.name, type: item.type }));
},
getTypeName(type) {
switch (type) {
case 2: return 'Numeric';
case 1: return 'Ordinal';
case 5: return 'Boolean';
case 7: return 'Ordinal';
default: return 'Numeric';
}
},
collectSelectedItems(items) {
let selectedItems = [];
for (const item of items) {
if (item.checked) {
selectedItems.push(item.name);
console.log(`Selected item: ${item.name}, Type: ${item.type}, Title: ${item.title}`);
selectedItems.push({ name: item.name, type: item.type, title: item.title });
//console.log('Selected items in collectSelectedItems:', selectedItems); // Log selected items
}
if (item.children) {
selectedItems = selectedItems.concat(this.collectSelectedItems(item.children));
if (item.children && item.children.length > 0) {
const childSelectedItems = this.collectSelectedItems(item.children);
selectedItems = selectedItems.concat(childSelectedItems);
}
}
return selectedItems;
},
submitSelection() {
async submitSelection() {
const selectedItems = this.collectSelectedItems(this.items);
//console.log('Selected items in Submit:', selectedItems); // Log selected items
if (selectedItems.length < 2) {
alert('Please select at least two items before submitting.');
let nonBooleanCriteriaCount = 0;
let selectedItemsWithType = selectedItems.map(item => ({
name: item.name,
type: item.type,
title: item.title
}));
for (const item of selectedItemsWithType) {
console.log(`Item: ${item.name}, Type: ${item.type}`); // Add this line for debugging
if (item.type !== 5) { // Or item.type !== 'Boolean' depending on the actual format
nonBooleanCriteriaCount++;
}
}
//console.log('Non-boolean criteria count:', nonBooleanCriteriaCount); // Log non-boolean criteria count
console.log('selectedItemsWithType:', selectedItemsWithType);
if (selectedItemsWithType.length < 2) {
//console.log('Blocking submission due to insufficient criteria selection.');
alert('Please select at least two criteria to proceed.');
return;
}
// Emitting the selected items - useful if there's a parent component listening to this event
this.$emit('selected-items', selectedItems);
if (nonBooleanCriteriaCount < 2) {
//console.log('Blocking submission due to insufficient non-boolean criteria selection.');
alert('Please select at least two non-boolean criteria.');
return;
}
// Programmatic navigation to the DataGrid page, passing the selected items as route parameters
this.$router.push({ name: 'DataGrid', params: { selectedItems: selectedItems } });
// Save the selected items with types to Local Storage
localStorage.setItem('selectedCriteria', JSON.stringify(selectedItemsWithType));
// Emitting the selected items with types to the DataGrid.vue
// this.$emit('selected-items', selectedItemsWithType);
// Navigate to DataGrid.vue, passing only the item names as route parameters
const itemNames = selectedItemsWithType.map(item => item.name);
this.$router.push({ name: 'DataGrid', params: { selectedItems: itemNames } });
},
async postSelectedItems(selectedItems) {
const requestOptions = {
method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify({selectedItems}),
};
const response = await fetch('http://127.0.0.1:5000/process_selected_items', requestOptions);
const data = await response.json();
//console.log('Send Selected items to back', data);
this.selectedItemsFromBack = data;
},
},
goBackToHome() {
this.$router.push({ name: 'HomePage' });
}
}
};
</script>
@ -193,6 +237,8 @@ button {
border-radius: 4px;
cursor: pointer;
transition: background-color 0.3s ease;
margin-bottom: 10px;
margin-top: 10px;
}
button:hover {
@ -217,4 +263,5 @@ ul {
background-color: var(--light-gray-color);
color: var(--main-color);
}
</style>

54
cfsb-frontend/src/components/HomePage.vue
View File

@ -1,18 +1,45 @@
<script>
export default {
name: "HomePage"
name: "HomePage",
// methods: {
// async saveIds(appId, userId) {
// fetch(' http://127.0.0.1:5000/save_ids', {
// method: 'POST',
// headers: {
// 'Content-Type': 'application/json',
// },
// body: JSON.stringify({
// app_id: appId,
// user_id: userId,
// }),
// })
// .then(response => response.json())
// .then(data => {
// console.log('Success:', data);
// // Save to local storage
// localStorage.setItem('app_id', appId);
// localStorage.setItem('user_id', userId);
// })
// .catch((error) => {
// console.error('Error:', error);
// });
// }
// },
// mounted() {
// // Example usage
// // this.saveIds('d535cf554ea66fbebfc415ac837a5828', 'e3ff4006-be5f-4e00-bbe1-e49a88b2541a');
// },
}
</script>
<template>
<div class="container">
<div class="row p-4 text-center">
<div class="col col-12">
<h1 class="display-2">Welcome to <span style="color: var(--main-color);">NebulOus</span></h1>
<h1 class="display-2">Welcome to <span style="color: var(--main-color);">Cloud Fog Service Broker</span></h1>
</div>
</div>
<!--
<div class="row align-items-center">
<div class="col col-12 col-md-6 col-lg-6">
<p class="lead">Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.</p>
@ -30,7 +57,7 @@ export default {
<p class="lead">Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.</p>
</div>
</div>
-->
<div class="spacer-sm"></div>
<div class="row text-center p-4 bg-row border-radius-sm">
@ -43,7 +70,7 @@ export default {
<div class="row p-4 text-center">
<div class="col col-12">
<h2 class="display-4">How does it work</h2>
<h2 class="display-4">Architecture</h2>
</div>
<div class="col col-12">
<img src="/images/Broker.png" class="img-fluid border-radius-md" alt="...">
@ -54,9 +81,16 @@ export default {
</template>
<style scoped>
.bg-row {
background-color: var(--secondary-color);
button-primary:hover{
border: 2px #172135;
}
.bg-row {
background-color: #e9ebed;
}
.row{text-align: justify;
}
.img-fluid {
max-width: 75%;
height: auto;
}
</style>

406
cfsb-frontend/src/components/Results.vue
View File

@ -1,13 +1,16 @@
<template>
<div class="results-container">
<h2>Evaluation Results</h2>
<p class="description">
The scores have been rounded to the nearest two decimal places.
</p>
<div v-if="loading" class="loading">Loading...</div>
<div v-else>
<!-- Table for displaying the results -->
<table v-if="results.length > 0">
<thead>
<tr>
<th>Fog Node</th>
<th>Node</th>
<th>Score (%)</th>
<th>Ranking</th>
</tr>
@ -20,6 +23,8 @@
</tr>
</tbody>
</table>
<!-- Separator Line -->
<div class="separator-line"></div>
<!-- Chart Container -->
<div class="charts-container">
<div class="chart-wrapper">
@ -29,179 +34,270 @@
<canvas id="ranksChart"></canvas>
</div>
</div>
</div>
<!-- Separator Line -->
<div class="separator-line"></div>
<div class="button-container">
<button @click="goBackToWR">Add/Modify Weight Restrictions</button>
<button @click="saveProjectResults">Save Project</button>
</div>
</div>
<div class="button-container">
<button @click="goBackToWR">Add/Modify Weight Restrictions</button>
<button @click="saveProjectResults">Save Project</button>
</div>
</div>
</template>
</template>
<script>
import Chart from 'chart.js/auto';
<script>
export const backendURL = import.meta.env.VITE_BACKEND_URL;
const apiURL = backendURL;
import Chart from 'chart.js/auto';
export default {
data() {
return {
results: [],
loading: true,
deaScoresChart: null,
ranksChart: null,
};
},
mounted() {
this.fetchResults();
},
methods: {
goBackToWR() {
// Make sure 'WR' matches the name of the route in your router configuration
this.$router.push({ name: 'WR' });
export default {
data() {
return {
results: [],
loading: true,
deaScoresChart: null,
ranksChart: null,
gridData: null,
relativeWRData: null,
immediateWRData: null
};
},
saveProjectResults() {
// For now, this method is a placeholder
console.log('Save Project Results button clicked');
mounted() {
const resultsString = localStorage.getItem('evaluationResults');
try {
const data = JSON.parse(resultsString);
if (data && data.results) {
this.results = data.results;
this.createCharts();
this.loading = false;
} else {
console.error('Error fetching results: Data is not in the expected format.');
this.loading = false;
// Handle the error by navigating to a different page or displaying an error message
}
} catch (error) {
console.error('Error parsing JSON:', error);
// Handle parsing error by navigating to a different page or displaying an error message
this.loading = false;
}
},
fetchResults() {
fetch('http://127.0.0.1:5000/get-evaluation-results')
.then(response => response.json())
.then(data => {
this.results = data;
this.loading = false;
this.createCharts();
})
.catch(error => {
console.error('Error fetching results:', error);
this.loading = false;
methods: {
goBackToWR() {
// Make sure 'WR' matches the name of the route in your router configuration
this.$router.push({ name: 'WR' });
},
async saveProjectResults() {
if (confirm("Save Project?")) {
console.log('Save Project Results button clicked');
let array_data = []
// Application Id
let app_id = localStorage.getItem('fog_broker_app_id');
let appData = [
{app_id: app_id}
];
array_data.push(appData);
// Node Names
let NodeNamesFromStorage = localStorage.getItem('NodeNames');
let NodeNames = JSON.parse(NodeNamesFromStorage);
array_data.push(NodeNames);
// Selected Criteria
let selectedCriteriaFromStorage = localStorage.getItem('selectedCriteria');
let selectedCriteria = JSON.parse(selectedCriteriaFromStorage);
array_data.push(selectedCriteria);
// DataGrid Data
let gridDataFromStorage = localStorage.getItem('gridData');
let GridData = JSON.parse(gridDataFromStorage);
array_data.push(GridData);
// relativeWRData
let relativeWRDataFromStorage = localStorage.getItem('relativeWRData');
let relativeWRData = JSON.parse(relativeWRDataFromStorage);
array_data.push(relativeWRData);
//immediateWRData
let immediateWRDataFromStorage = localStorage.getItem('immediateWRData');
let immediateWRData = JSON.parse(immediateWRDataFromStorage);
array_data.push(immediateWRData);
// evaluation Results
let evaluationResultsFromStorage = localStorage.getItem('evaluationResults');
let evaluationResults = JSON.parse(evaluationResultsFromStorage);
array_data.push(evaluationResults.results); // Save only th results not the LPStatus
let result = await this.saveProjectData(array_data);
console.log(result);
// Clear local storage
localStorage.removeItem('evaluationResults');
localStorage.removeItem('selectedCriteria');
localStorage.removeItem('NodeNames');
localStorage.removeItem('gridData');
localStorage.removeItem('relativeWRData');
localStorage.removeItem('immediateWRData');
// localStorage.removeItem('fog_broker_user_uuid'); May keep them so the user can evaluate again
// localStorage.removeItem('fog_broker_app_id');
// Redirect to the Home page
this.$router.push({ name: 'HomePage' });
}
else {
console.log('Project not saved.');
}
},
async saveProjectData(data) {
try {
const response = await fetch(apiURL+'/app/save', {
method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify(data)
});
},
createCharts() {
const titles = this.results.map(result => result.Title);
const deaScores = this.results.map(result => result['DEA Score']);
const ranks = this.results.map(result => result.Rank);
console.log("response" + response);
let response_data = await response.json();
console.log(response_data);
} catch (error) {
console.error('Error saving project:', error);
}
},
createCharts() {
if (!this.results || this.results.length === 0) {
console.error('No results data available to create charts.');
return;
}
console.log(this.results);
this.$nextTick(() => {
this.createBarChart(titles, deaScores, 'deascoresChart', 'Fog Node Scores');
this.createHorizontalBarChart(titles, ranks, 'ranksChart', 'Fog Node Ranking');
});
},
createBarChart(labels, data, chartId, label) {
const ctx = document.getElementById(chartId).getContext('2d');
if (this.deaScoresChart) {
this.deaScoresChart.destroy();
}
this.deaScoresChart = new Chart(ctx, {
type: 'bar',
data: {
labels,
datasets: [{
label,
data,
backgroundColor: 'rgba(181,141,243,0.56)',
borderColor: 'rgb(102,16,242)',
borderWidth: 1
}]
},
options: {
responsive: true,
//maintainAspectRatio: false,
scales: {
y: {
beginAtZero: true,
max: 1, // Set the maximum value of the y-axis to 1
}
const titles = this.results.map(result => result.Title);
const deaScores = this.results.map(result => result['DEA Score']);
const ranks = this.results.map(result => result.Rank);
this.$nextTick(() => {
this.createBarChart(titles, deaScores, 'deascoresChart', 'Fog Node Scores');
this.createHorizontalBarChart(titles, ranks, 'ranksChart', 'Fog Node Ranking');
});
},
createBarChart(labels, data, chartId, label) {
const ctx = document.getElementById(chartId).getContext('2d');
if (this.deaScoresChart) {
this.deaScoresChart.destroy();
}
this.deaScoresChart = new Chart(ctx, {
type: 'bar',
data: {
labels,
datasets: [{
label,
data,
backgroundColor: 'rgba(181,141,243,0.56)',
borderColor: 'rgb(102,16,242)',
borderWidth: 1
}]
},
plugins: {
tooltip: {
callbacks: {
label: function(tooltipItem) {
let score = tooltipItem.raw * 100;
return `Score: ${score.toFixed(2)}%`;
}
},
bodyFontSize: 16, // Adjust font size as needed
titleFontSize: 16
options: {
responsive: true,
//maintainAspectRatio: false,
scales: {
y: {
beginAtZero: true,
max: 1, // Set the maximum value of the y-axis to 1
}
},
plugins: {
tooltip: {
callbacks: {
label: function(tooltipItem) {
let score = tooltipItem.raw * 100;
return `Score: ${score.toFixed(2)}%`;
}
},
bodyFontSize: 16, // Adjust font size as needed
titleFontSize: 16
}
}
}
});
},
createHorizontalBarChart(labels, data, chartId, label) {
const ctx = document.getElementById(chartId).getContext('2d');
if (this.ranksChart) {
this.ranksChart.destroy();
}
});
},
createHorizontalBarChart(labels, data, chartId, label) {
const ctx = document.getElementById(chartId).getContext('2d');
if (this.ranksChart) {
this.ranksChart.destroy();
}
// Assuming higher scores should have longer bars, so we invert the scores
// as higher rank should have lower numerical value
const invertedData = data.map(score => Math.max(...data) - score + Math.min(...data));
this.ranksChart = new Chart(ctx, {
type: 'bar', // In Chart.js 3.x, you specify horizontal bars using indexAxis
data: {
labels,
datasets: [{
label,
data: invertedData,
backgroundColor: 'rgba(110,108,229,0.55)',
borderColor: 'rgb(60,54,235)',
borderWidth: 1
}]
},
options: {
responsive: true,
//maintainAspectRatio: false, // Set to false to allow full width and controlled height
indexAxis: 'y', // This will make the bar chart horizontal
scales: {
x: {
beginAtZero: true
}
// Assuming higher scores should have longer bars, so we invert the scores
// as higher rank should have lower numerical value
const invertedData = data.map(score => Math.max(...data) - score + Math.min(...data));
this.ranksChart = new Chart(ctx, {
type: 'bar', // In Chart.js 3.x, you specify horizontal bars using indexAxis
data: {
labels,
datasets: [{
label,
data: invertedData,
backgroundColor: 'rgba(110,108,229,0.55)',
borderColor: 'rgb(60,54,235)',
borderWidth: 1
}]
},
plugins: {
tooltip: {
callbacks: {
label: function(context) {
// Since we inverted the data, we need to correct the value displayed in the tooltip
const rankValue = Math.max(...data) - context.parsed.x + Math.min(...data);
return `Rank: ${rankValue}`;
}
},
bodyFontSize: 16, // Adjust font size as needed
titleFontSize: 16
options: {
responsive: true,
//maintainAspectRatio: false, // Set to false to allow full width and controlled height
indexAxis: 'y', // This makes the bar chart horizontal
scales: {
x: {
beginAtZero: true
}
},
plugins: {
tooltip: {
callbacks: {
label: function(context) {
// Since we inverted the data, we need to correct the value displayed in the tooltip
const rankValue = Math.max(...data) - context.parsed.x + Math.min(...data);
return `Rank: ${rankValue}`;
}
},
bodyFontSize: 16, // Adjust font size as needed
titleFontSize: 16
}
}
}
}
});
},
formatPercentage(value) {
const percentage = (value * 100).toFixed(2);
return percentage === '100.00' ? '100%' : `${percentage}%`;
});
},
formatPercentage(value) {
const percentage = (value * 100).toFixed(2);
return percentage === '100.00' ? '100%' : `${percentage}%`;
}
}
};
</script>
<style>
.results-container {
padding: 20px;
}
};
</script>
<style>
.results-container {
padding: 20px;
}
.loading {
text-align: center;
}
.loading {
text-align: center;
}
.charts-container {
display: flex;
flex-direction: row; /* Align charts horizontally */
justify-content: space-around;
padding: 0 20px; /* Add padding if needed */
}
.charts-container {
display: flex;
flex-direction: row; /* Align charts horizontally */
justify-content: space-around;
padding: 0 20px; /* Add padding if needed */
}
.chart-wrapper {
flex: 1; /* Each chart will take equal space */
/* Remove max-width or set it to a higher value if you want a specific limit */
margin: auto;
}
.chart-wrapper {
flex: 1; /* Each chart will take equal space */
/* Remove max-width or set it to a higher value if you want a specific limit */
margin: auto;
}
td {
text-align: center;
}
td {
text-align: center;
}
.separator-line {
height: 4px; /* Thickness of the line */
background-color: #172135; /* Deep purple color */
margin: 10px 0; /* Spacing above and below the line */
}
</style>
</style>

397
cfsb-frontend/src/components/WR.vue
View File

@ -1,97 +1,177 @@
<template>
<div class="wr-container">
<div v-for="(condition, index) in conditions" :key="index" class="condition-row">
<select v-model="condition.column1" @change="updateDropdowns(index)">
<option value="" disabled>Select Criterion</option>
<option v-for="col in availableColumns(index, 1)" :key="`1-${col}`" :value="col">{{ col }}</option>
</select>
<!-- Relative constraints section -->
<div class="relative-constraints">
<h2>Relative Constraints</h2>
<p class="description">
Set relative constraints between the criteria. For example, "Weight of Criterion A >= 2* Weight of Criterion B".
</p>
<div v-for="(condition, index) in relativeConditions" :key="index" class="condition-row">
<select v-model="condition.column1" @change="updateDropdowns(index)">
<option value="" disabled>Select Criterion</option>
<option v-for="col in availableColumns(index, 1)" :key="`1-${col}`" :value="col">{{ col }}</option>
</select>
<select v-model="condition.operator">
<option value="" disabled>Select Operator</option>
<option v-for="op in operators" :key="op" :value="op">{{ op }}</option>
</select>
<select v-model="condition.operator">
<option value="" disabled>Select Operator</option>
<option v-for="op in operators" :key="op" :value="op">{{ op }}</option>
</select>
<input type="number" v-model.number="condition.value" :min="0" placeholder="Value" />
<!-- <select v-model="condition.operator">-->
<!-- <option value="" disabled>Select Operator</option>-->
<!-- <option v-for="(value, key) in operatorMapping" :key="key" :value="value">{{ key }}</option>-->
<!-- </select>-->
<select v-model="condition.column2" @change="updateDropdowns(index)">
<option value="" disabled>Select Criterion</option>
<option v-for="col in availableColumns(index, 2)" :key="`2-${col}`" :value="col">{{ col }}</option>
</select>
<input type="number" v-model.number="condition.value" :min="0" step="0.5" placeholder="Value" />
<button @click="removeCondition(index)">-</button>
<select v-model="condition.column2" @change="updateDropdowns(index)">
<option value="" disabled>Select Criterion</option>
<option v-for="col in availableColumns(index, 2)" :key="`2-${col}`" :value="col">{{ col }}</option>
</select>
<button @click="removeCondition(index)">-</button>
</div>
<button @click="addCondition">+ Add Relative Constraint</button>
</div>
<!-- Separator Line -->
<div class="separator-line"></div>
<div class="immediate-constraints">
<h2>Immediate Constraints</h2>
<p class="description">
Set immediate constraints on individual criteria. For example, "Weight of Criterion A >= 0.25".
</p>
<div v-for="(immediateCondition, index) in immediateConditions" :key="`immediate-${index}`" class="condition-row">
<select v-model="immediateCondition.criterion">
<option value="" disabled>Select Criterion</option>
<option v-for="col in criteria_titles" :key="`immediate-${col}`" :value="col">{{ col }}</option>
</select>
<button @click="addCondition">+</button>
<!-- <button @click.prevent="sendWRData">Run Evaluation</button> -->
<button @click="sendWRData">Run Evaluation</button>
<select v-model="immediateCondition.operator">
<option value="" disabled>Select Operator</option>
<option v-for="op in operators" :key="op" :value="op">{{ op }}</option>
</select>
<!-- <select v-model="immediateCondition.operator">-->
<!-- <option value="" disabled>Select Operator</option>-->
<!-- <option v-for="(value, key) in operatorMapping" :key="key" :value="value">{{ key }}</option>-->
<!-- </select>-->
<input type="number" v-model.number="immediateCondition.value" :min="0" step="0.1" placeholder="Value" />
<button @click="removeImmediateCondition(index)">-</button>
</div>
<button @click="addImmediateCondition">+ Add Immediate Constraint</button>
</div>
<!-- Separator Line -->
<div class="separator-line"></div>
<div class="pt-4"></div>
<div class="button-container">
<button @click="goBackToCriteriaSelection" class="bg-color-primary">Back to Criteria Selection</button>
<button @click="sendWRData" class="bg-color-primary">Run Evaluation</button>
</div>
</div>
</template>
<script>
import { useRouter } from 'vue-router';
export const backendURL = import.meta.env.VITE_BACKEND_URL;
const apiURL = backendURL;
export default {
data() {
return {
receivedGridData: null,
conditions: [{ column1: '', operator: '', value: 0, column2: '' }],
relativeConditions: [{ column1: '', operator: '', value: 0, column2: '' }],
criteria_titles: [], // This is populated with the column titles
operators: ['>=', '=', '<='],
immediateConditions: [{ criterion: '', operator: '', value: 0 }],
operatorMapping: {
'>=': 1,
'=': 0,
'<=': -1
},
errorMessage: '', // Add this line
};
},
mounted() {
// Prioritize data from route parameters
if (this.$route.params.data) {
// Parse the JSON string back into an object
this.receivedGridData = JSON.parse(this.$route.params.data);
} else {
// Fallback to localStorage if route params are not available
const gridDataFromStorage = localStorage.getItem('gridData');
if (gridDataFromStorage) {
this.receivedGridData = JSON.parse(gridDataFromStorage);
}
}
// Continue with other localStorage checks
const wrDataFromStorage = localStorage.getItem('wrData');
const immediateWRDataFromStorage = localStorage.getItem('immediateWRData');
if (wrDataFromStorage) {
this.wrData = JSON.parse(wrDataFromStorage);
}
if (immediateWRDataFromStorage) {
this.immediateConditions = JSON.parse(immediateWRDataFromStorage);
} else {
this.immediateConditions = [{ criterion: '', operator: '', value: 0 }];
}
// Retrieve selectedCriteria from local storage
const selectedCriteriaJson = localStorage.getItem('selectedCriteria');
if (selectedCriteriaJson) {
try {
const selectedCriteria = JSON.parse(selectedCriteriaJson);
// Use selectedCriteria to populate criteria_titles and filter out boolean criteria (type 5)
this.criteria_titles = selectedCriteria
.filter(info => info.type !== 5)
.map(info => info.title);
} catch (e) {
console.error('Error parsing selected criteria information:', e);
this.$router.push({ name: 'CriteriaSelection' });
}
} else {
console.error('Error: Selected criteria information not found in local storage.');
this.$router.push({ name: 'CriteriaSelection' });
}
console.log('WR.vue Received gridData:', this.receivedGridData);
this.fetchCriteriaTitles();
},
methods: {
fetchCriteriaTitles() {
fetch('http://127.0.0.1:5000/get-criteria-titles')
.then(response => {
if (!response.ok) {
throw new Error(`HTTP error! status: ${response.status}`);
}
return response.json();
})
.then(data => {
this.criteria_titles = data;
})
.catch(error => {
console.error('Error fetching criteria titles:', error);
});
},
addCondition() {
this.conditions.push({column1: '', column2: '', operator: '', value: 0});
this.relativeConditions.push({column1: '', column2: '', operator: '', value: 0});
},
removeCondition(index) {
this.conditions.splice(index, 1);
this.relativeConditions.splice(index, 1);
},
validateForm() {
for (const condition of this.conditions) {
for (const condition of this.relativeConditions) {
if (!condition.column1 || !condition.column2) {
alert('Please select criteria for each relative constraint.');
return false;
}
if (!condition.operator) {
alert('Please select an operator for each condition.');
alert('Please select an operator for each relative constraint.');
return false;
}
if (condition.value === null || condition.value === '') {
alert('Please enter a numeric value for each.');
alert('Please enter a numeric value for each relative constraint.');
return false;
}
if (condition.value < 0) {
alert('Values cannot be less than zero.');
return false;
}
const uniquePairs = new Set(
this.conditions.map(c => [c.column1, c.column2].sort().join('-'))
);
if (uniquePairs.size !== this.conditions.length) {
alert('Each pair of criteria can only be used once in a restriction!');
if (condition.value <= 0) {
alert('The priority in each relative constraint must be greater than zero.');
return false;
}
}
const uniquePairs = new Set(
this.relativeConditions.map(c => [c.column1, c.column2].sort().join('-'))
);
if (uniquePairs.size !== this.relativeConditions.length) {
alert('Each pair of criteria can only be used once in a restriction!');
return false;
}
return true;
},
updateDropdowns(index) {
@ -100,15 +180,73 @@ export default {
availableColumns(index, dropdownNumber) {
if (dropdownNumber === 1) {
// For the first dropdown, filter out the column selected in the second dropdown
return this.criteria_titles.filter(col => col !== this.conditions[index].column2);
return this.criteria_titles.filter(col => col !== this.relativeConditions[index].column2);
} else {
// For the second dropdown, filter out the column selected in the first dropdown
return this.criteria_titles.filter(col => col !== this.conditions[index].column1);
return this.criteria_titles.filter(col => col !== this.relativeConditions[index].column1);
}
},
// Add a method to validate the Immediate Constraints
validateImmediateConstraints() {
let criterionConstraints = {};
// Iterate over immediate conditions and organize them by criterion
for (const condition of this.immediateConditions) {
if (!condition.criterion || !condition.operator) {
continue; // Skip empty conditions
}
// Ensure value is greater than 0
if (condition.value === null || condition.value === '' || condition.value <= 0) {
alert(`The importance of criterion "${condition.criterion}" should be greater than 0.`);
return false;
}
// Initialize the constraints list for the criterion if not already done
if (!criterionConstraints[condition.criterion]) {
criterionConstraints[condition.criterion] = {};
}
// Check for duplicate operators
if (criterionConstraints[condition.criterion][condition.operator]) {
alert(`You cannot use the same operator more than once for the criterion "${condition.criterion}".`);
return false;
}
// Add the condition to the list for the criterion
criterionConstraints[condition.criterion][condition.operator] = condition.value;
}
// Iterate over the constraints for each criterion and apply validation rules
for (const [criterion, operators] of Object.entries(criterionConstraints)) {
// Only one constraint allowed when using '=' operator
if (operators['='] !== undefined && Object.keys(operators).length > 1) {
alert(`Only one constraint allowed for '${criterion}' when using '=' operator.`);
return false;
}
// Validate logical consistency between '>=' and '<=' values
if (operators['>='] !== undefined && operators['<='] !== undefined) {
const greaterThanOrEqualValue = parseFloat(operators['>=']);
const lessThanOrEqualValue = parseFloat(operators['<=']);
if (isNaN(greaterThanOrEqualValue) || isNaN(lessThanOrEqualValue)) {
alert(`Invalid numeric values for the criterion "${criterion}".`);
return false;
}
if (greaterThanOrEqualValue > lessThanOrEqualValue) {
alert(`For the criterion "${criterion}", the value for '>=' must be less than or equal to the value for '<='.`);
return false;
}
}
}
return true;
},
validateNonInvertedConditions() {
let isValid = true;
let conditionPairs = this.conditions.map(c => [c.column1, c.column2].sort().join('-'));
let conditionPairs = this.relativeConditions.map(c => [c.column1, c.column2].sort().join('-'));
// Create a Set for unique pairs
const uniquePairs = new Set(conditionPairs);
@ -120,94 +258,122 @@ export default {
return isValid;
},
addImmediateCondition() {
this.immediateConditions.push({ criterion: '', operator: '', value: 0 });
},
removeImmediateCondition(index) {
this.immediateConditions.splice(index, 1);
},
async sendWRData() {
// Check if any condition is set
const isAnyConditionSet = this.conditions.some(condition => condition.column1 && condition.column2 && condition.operator);
// Check if any relative or immediate condition is set
const isAnyRelativeConditionSet = this.relativeConditions.some(condition => condition.column1 && condition.column2 && condition.operator);
const isAnyImmediateConditionSet = this.immediateConditions.some(condition => condition.criterion && condition.operator);
// If no conditions are set, prompt the user
if (!isAnyConditionSet) {
// Filter out incomplete or empty relative constraints
const validRelativeConditions = this.relativeConditions.filter(condition => condition.column1 && condition.column2 && condition.operator);
// Filter out incomplete or empty immediate constraints
const validImmediateConditions = this.immediateConditions.filter(condition => condition.criterion && condition.operator);
// Prompt the user if no conditions are set
if (!isAnyRelativeConditionSet && !isAnyImmediateConditionSet) {
const proceedWithoutWR = confirm("Would you like to proceed without imposing Weight Restrictions?");
if (!proceedWithoutWR) {
// User chose 'No', do nothing to stay on the current page
return;
return; // User chose 'No', do nothing
}
// User chose 'Yes', proceed with sending data
// Clear data if user chose 'Yes'
this.relativeConditions = [];
this.immediateConditions = [];
} else {
// Validate the form only if there are conditions set
if (!this.validateForm() || !this.validateNonInvertedConditions()) {
alert('Invalid Weight Restrictions, each pair of criteria can be used only once!');
// Validate conditions
if ((isAnyRelativeConditionSet && (!this.validateForm() || !this.validateNonInvertedConditions())) ||
(isAnyImmediateConditionSet && (!this.validateImmediateConstraints()))) {
return; // Stop if validation fails
}
}
const operatorMapping = {
'<=': -1,
'=': 0,
'>=': 1
};
// Process Relative constraints
const relativeWRData = validRelativeConditions.map(condition => ({
LHSCriterion: condition.column1,
Operator: this.operatorMapping[condition.operator],
Intense: condition.value,
RHSCriterion: condition.column2
}));
const processedWRData = this.conditions.map(condition => {
return {
LHSCriterion: condition.column1,
Operator: operatorMapping[condition.operator],
Intense: condition.value,
RHSCriterion: condition.column2
};
});
// Process Immediate constraints
const immediateWRData = validImmediateConditions.map(condition => ({
Criterion: condition.criterion,
Operator: this.operatorMapping[condition.operator],
Value: condition.value
}));
// Retrieve node names from local storage
let nodeNamesArray = [];
const NodeNamesString = localStorage.getItem('NodeNames');
if (NodeNamesString) {
nodeNamesArray = JSON.parse(NodeNamesString);
}
// Prepare payload with filtered conditions
const payload = {
gridData: this.receivedGridData, // Data received from DataGrid.vue
wrData: processedWRData
gridData: this.receivedGridData,
relativeWRData: relativeWRData,
immediateWRData: immediateWRData,
nodeNames: nodeNamesArray
};
console.log('Payload being sent to backend from WR.vue:', payload);
// Ask the backend to perform evaluation
try {
const response = await fetch('http://127.0.0.1:5000/process-evaluation-data', {
const response = await fetch(apiURL+'/process-evaluation-data', {
method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify(payload)
});
const data = await response.json();
console.log('Response from backend:', data);
if (!response.ok) {
// If the HTTP response is not OK, throw an error
throw new Error('Network response was not ok');
}
// Check if the response was successful
if (response.ok && data.status === 'success') {
// Redirect to Results.vue
this.$router.push({ name: 'Results' });
} /*else {
// Handle error
console.error('Error in response:', data.message);
alert('Failed to process data: ' + data.message);
} */
const data = await response.json();
console.log('Response from backend process-evaluation-data():', data);
console.log('Response data.results.LPstatus:', data.results.LPstatus);
// First, check the general status of the response to confirm the request was processed successfully
// Check the LP problem's feasibility status
if (data.status === 'success') {
if (data.results.LPstatus === 'feasible') {
localStorage.setItem('evaluationResults', JSON.stringify(data.results));
localStorage.setItem('relativeWRData', JSON.stringify(relativeWRData));
localStorage.setItem('immediateWRData', JSON.stringify(immediateWRData));
// Navigate to Results.vue
this.$router.push({ name: 'Results', params: { evaluationResults: data.results.results } });
} else if (data.results.LPstatus === 'infeasible') {
// Set the error message for infeasible LP solution
this.errorMessage = data.results.message; // Accessing the message directly
alert(this.errorMessage); // Show the message to the user via alert
}
} else {
// Handle other unexpected 'status'
this.errorMessage = 'An unexpected error occurred.';
}
} catch (error) {
console.error('Error sending data to backend:', error);
alert('Failed to send data to backend.');
console.error('Error:', error);
this.errorMessage = error.message || 'Failed to send data to backend.';
}
},
sendDataToBackend(payload) {
console.log('Sending payload to backend:', payload);
fetch('http://127.0.0.1:5000/process-evaluation-data', {
method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify(payload)
})
.then(response => {
console.log('Raw response:', response);
return response.json();
})
.then(data => {
console.log('Response from backend:', data);
// Handle the response from the backend
})
.catch(error => {
console.error('Error sending data to backend:', error);
});
goBackToCriteriaSelection() {
this.$router.push({ name: 'CriteriaSelection' });
}
}
};
</script>
<style scoped>
input{height: 40px;}
.wr-container {
display: flex;
flex-direction: column;
@ -218,6 +384,7 @@ export default {
display: flex;
align-items: center;
gap: 10px;
margin-bottom: 15px;
}
button {
@ -233,7 +400,7 @@ button {
button:hover {
background-color: var(--secondary-color); /* Lighter shade of purple on hover */
color: var(--main-color);
border:2px;
border-color:var(--main-color);
border: 2px;
border-color: var(--main-color);
}
</style>

357
cfsb-frontend/src/components/WR_AllCriteria.vue Normal file
View File

@ -0,0 +1,357 @@
<template>
<div class="wr-container">
<!-- Relative constraints section -->
<div class="relative-constraints">
<h3>Relative Constraints</h3>
<p class="description">
Set relative constraints between the criteria. For example, "Weight of Criterion A >= 2* Weight of Criterion B".
</p>
<div v-for="(condition, index) in relativeConditions" :key="index" class="condition-row">
<select v-model="condition.column1" @change="updateDropdowns(index)">
<option value="" disabled>Select Criterion</option>
<option v-for="col in availableColumns(index, 1)" :key="`1-${col}`" :value="col">{{ col }}</option>
</select>
<select v-model="condition.operator">
<option value="" disabled>Select Operator</option>
<option v-for="op in operators" :key="op" :value="op">{{ op }}</option>
</select>
<input type="number" v-model.number="condition.value" :min="0" step="0.5" placeholder="Value" />
<select v-model="condition.column2" @change="updateDropdowns(index)">
<option value="" disabled>Select Criterion</option>
<option v-for="col in availableColumns(index, 2)" :key="`2-${col}`" :value="col">{{ col }}</option>
</select>
<button @click="removeCondition(index)">-</button>
</div>
<button @click="addCondition">+ Add Relative Constraint</button>
</div>
<div class="immediate-constraints">
<h3>Immediate Constraints</h3>
<p class="description">
Set immediate constraints on individual criteria. For example, "Weight of Criterion A >= 0.25".
</p>
<div v-for="(immediateCondition, index) in immediateConditions" :key="`immediate-${index}`" class="condition-row">
<select v-model="immediateCondition.criterion">
<option value="" disabled>Select Criterion</option>
<option v-for="col in criteria_titles" :key="`immediate-${col}`" :value="col">{{ col }}</option>
</select>
<select v-model="immediateCondition.operator">
<option value="" disabled>Select Operator</option>
<option v-for="op in operators" :key="op" :value="op">{{ op }}</option>
</select>
<input type="number" v-model.number="immediateCondition.value" :min="0" step="0.1" placeholder="Value" />
<button @click="removeImmediateCondition(index)">-</button>
</div>
<button @click="addImmediateCondition">+ Add Immediate Constraint</button>
</div>
<button @click="sendWRData">Run Evaluation</button>
</div>
</template>
<script>
export const backendURL = import.meta.env.VITE_BACKEND_URL;
const apiURL = backendURL;
import {useRouter} from 'vue-router';
export default {
data() {
return {
receivedGridData: null,
relativeConditions: [{column1: '', operator: '', value: 0, column2: ''}],
criteria_titles: [], // This is populated with the column titles
operators: ['>=', '=', '<='],
immediateConditions: [{criterion: '', operator: '', value: 0}],
operatorMapping: {
'<=': -1,
'=': 0,
'>=': 1
},
};
},
mounted() {
if (this.$route.params.data) {
// Parse the JSON string back into an object
this.receivedGridData = JSON.parse(this.$route.params.data);
}
const gridDataFromStorage = localStorage.getItem('gridData');
const wrDataFromStorage = localStorage.getItem('wrData');
const immediateWRDataFromStorage = localStorage.getItem('immediateWRData');
if (gridDataFromStorage) {
this.receivedGridData = JSON.parse(gridDataFromStorage);
}
if (wrDataFromStorage) {
this.wrData = JSON.parse(wrDataFromStorage);
}
if (immediateWRDataFromStorage) {
this.immediateConditions = JSON.parse(immediateWRDataFromStorage);
} else {
// Reset immediateConditions if there is no stored data
this.immediateConditions = [{criterion: '', operator: '', value: 0}];
}
this.fetchCriteriaTitles();
},
methods: {
fetchCriteriaTitles() {
fetch(apiURL+'/get-criteria-titles')
.then(response => {
if (!response.ok) {
throw new Error(`HTTP error! status: ${response.status}`);
}
return response.json();
})
.then(data => {
this.criteria_titles = data;
})
.catch(error => {
console.error('Error fetching criteria titles:', error);
});
},
addCondition() {
this.relativeConditions.push({column1: '', column2: '', operator: '', value: 0});
},
removeCondition(index) {
this.relativeConditions.splice(index, 1);
},
validateForm() {
for (const condition of this.relativeConditions) {
if (!condition.column1 || !condition.column2) {
alert('Please select criteria for each relative constraint.');
return false;
}
if (!condition.operator) {
alert('Please select an operator for each relative constraint.');
return false;
}
if (condition.value === null || condition.value === '') {
alert('Please enter a numeric value for each relative constraint.');
return false;
}
if (condition.value <= 0) {
alert('The priority in each relative constraint must be greater than zero.');
return false;
}
}
const uniquePairs = new Set(
this.relativeConditions.map(c => [c.column1, c.column2].sort().join('-'))
);
if (uniquePairs.size !== this.relativeConditions.length) {
alert('Each pair of criteria can only be used once in a restriction!');
return false;
}
return true;
},
updateDropdowns(index) {
// May be used to update dropdown availability
},
availableColumns(index, dropdownNumber) {
if (dropdownNumber === 1) {
// For the first dropdown, filter out the column selected in the second dropdown
return this.criteria_titles.filter(col => col !== this.relativeConditions[index].column2);
} else {
// For the second dropdown, filter out the column selected in the first dropdown
return this.criteria_titles.filter(col => col !== this.relativeConditions[index].column1);
}
},
// Add a method to validate the Immediate Constraints
validateImmediateConstraints() {
let criterionConstraints = {};
// Iterate over immediate conditions and organize them by criterion
for (const condition of this.immediateConditions) {
if (!condition.criterion || !condition.operator) {
continue; // Skip empty conditions
}
// Ensure value is greater than 0
if (condition.value === null || condition.value === '' || condition.value <= 0) {
alert(`The importance of criterion "${condition.criterion}" should be greater than 0.`);
return false;
}
// Initialize the constraints list for the criterion if not already done
if (!criterionConstraints[condition.criterion]) {
criterionConstraints[condition.criterion] = {};
}
// Check for duplicate operators
if (criterionConstraints[condition.criterion][condition.operator]) {
alert(`You cannot use the same operator more than once for the criterion "${condition.criterion}".`);
return false;
}
// Add the condition to the list for the criterion
criterionConstraints[condition.criterion][condition.operator] = condition.value;
}
// Iterate over the constraints for each criterion and apply validation rules
for (const [criterion, operators] of Object.entries(criterionConstraints)) {
// Only one constraint allowed when using '=' operator
if (operators['='] !== undefined && Object.keys(operators).length > 1) {
alert(`Only one constraint allowed for '${criterion}' when using '=' operator.`);
return false;
}
// Validate logical consistency between '>=' and '<=' values
if (operators['>='] !== undefined && operators['<='] !== undefined) {
const greaterThanOrEqualValue = parseFloat(operators['>=']);
const lessThanOrEqualValue = parseFloat(operators['<=']);
if (isNaN(greaterThanOrEqualValue) || isNaN(lessThanOrEqualValue)) {
alert(`Invalid numeric values for the criterion "${criterion}".`);
return false;
}
if (greaterThanOrEqualValue > lessThanOrEqualValue) {
alert(`For the criterion "${criterion}", the value for '>=' must be less than or equal to the value for '<='.`);
return false;
}
}
}
return true;
},
validateNonInvertedConditions() {
let isValid = true;
let conditionPairs = this.relativeConditions.map(c => [c.column1, c.column2].sort().join('-'));
// Create a Set for unique pairs
const uniquePairs = new Set(conditionPairs);
if (uniquePairs.size !== conditionPairs.length) {
// There are duplicates
isValid = false;
}
return isValid;
},
addImmediateCondition() {
this.immediateConditions.push({criterion: '', operator: '', value: 0});
},
removeImmediateCondition(index) {
this.immediateConditions.splice(index, 1);
},
async sendWRData() {
const operatorMapping = {'<=': -1, '=': 0, '>=': 1};
// Check if any relative or immediate condition is set
const isAnyRelativeConditionSet = this.relativeConditions.some(condition => condition.column1 && condition.column2 && condition.operator);
const isAnyImmediateConditionSet = this.immediateConditions.some(condition => condition.criterion && condition.operator);
// Filter out incomplete or empty relative constraints
const validRelativeConditions = this.relativeConditions.filter(condition => condition.column1 && condition.column2 && condition.operator);
// Filter out incomplete or empty immediate constraints
const validImmediateConditions = this.immediateConditions.filter(condition => condition.criterion && condition.operator);
// Prompt the user if no conditions are set
if (!isAnyRelativeConditionSet && !isAnyImmediateConditionSet) {
const proceedWithoutWR = confirm("Would you like to proceed without imposing Weight Restrictions?");
if (!proceedWithoutWR) {
return; // User chose 'No', do nothing
}
// Clear data if user chose 'Yes'
this.relativeConditions = [];
this.immediateConditions = [];
} else {
// Validate conditions
if ((isAnyRelativeConditionSet && (!this.validateForm() || !this.validateNonInvertedConditions())) ||
(isAnyImmediateConditionSet && (!this.validateImmediateConstraints()))) {
return; // Stop if validation fails
}
}
// Process Relative constraints
const RelativeWRData = validRelativeConditions.map(condition => ({
LHSCriterion: condition.column1,
Operator: this.operatorMapping[condition.operator],
Intense: condition.value,
RHSCriterion: condition.column2
}));
// Process Immediate constraints
const immediateWRData = validImmediateConditions.map(condition => ({
Criterion: condition.criterion,
Operator: this.operatorMapping[condition.operator],
Value: condition.value
}));
// Prepare payload with filtered conditions
const payload = {
gridData: this.receivedGridData,
wrData: RelativeWRData,
immediateWRData: immediateWRData
};
try {
const response = await fetch(apiURL+'/process-evaluation-data', {
method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify(payload)
});
const data = await response.json();
console.log('Response from backend:', data);
// Check if the response was successful
if (response.ok && data.status === 'success') {
localStorage.setItem('gridData', JSON.stringify(this.receivedGridData));
localStorage.setItem('wrData', JSON.stringify(RelativeWRData));
this.$router.push({name: 'Results'});
} else {
console.error('Error in response:', data.message);
alert('Failed to process data: ' + data.message);
}
} catch (error) {
console.error('Error sending data to backend:', error);
alert('Failed to send data to backend.');
}
}
}
};
</script>
<style scoped>
.wr-container {
display: flex;
flex-direction: column;
gap: 10px;
}
.condition-row {
display: flex;
align-items: center;
gap: 10px;
}
button {
background-color: var(--main-color); /* Blue color */
color: #fff; /* White text color */
padding: 10px 15px;
border: none;
border-radius: 4px;
cursor: pointer;
transition: background-color 0.3s ease;
}
button:hover {
background-color: var(--secondary-color); /* Lighter shade of purple on hover */
color: var(--main-color);
border: 2px;
border-color: var(--main-color);
}
</style>

1
cfsb-frontend/src/index.js
View File

@ -1,7 +1,6 @@
import { createRouter, createWebHistory } from 'vue-router';
import DataGrid from '@/components/DataGrid.vue';
import CriteriaSelection from '@/components/CriteriaSelection.vue'; // Import the new component
//import SummedData from '@/components/SummedData.vue';
import Evaluation from '@/components/Evaluation.vue'; // Import the Evaluation component
import WR from '@/components/WR.vue';
import Results from '@/components/Results.vue'; // Import the Results component

1
cfsb-frontend/src/router.js
View File

@ -1,4 +1,3 @@
// router.js
import { createRouter, createWebHistory } from 'vue-router';
import App from './App.vue';
import HierarchicalCategoryList from '@/components/HierarchicalCategoryList.vue';

23
charts/nebulous-cloud-fog-service-broker/templates/config-map-postgresql.yaml Normal file
View File

@ -0,0 +1,23 @@
apiVersion: v1
kind: ConfigMap
metadata:
name: db-init-script
data:
db_script.sql: |
CREATE TABLE IF NOT EXISTS users (
id SERIAL PRIMARY KEY,
uuid VARCHAR(255) NOT NULL,
username VARCHAR(255) NOT NULL,
password VARCHAR(255) NOT NULL
);
CREATE TABLE IF NOT EXISTS apps (
id SERIAL PRIMARY KEY,
user_uuid VARCHAR(255) NOT NULL,
title VARCHAR(255) NOT NULL,
description TEXT,
app_id VARCHAR(255) NOT NULL
);
INSERT INTO users (username, password, uuid) VALUES ('greg', '12345', 'e3ff4006-be5f-4e00-bbe1-e49a88b2541a');
INSERT INTO apps (user_uuid, title, description, app_id) VALUES ('e3ff4006-be5f-4e00-bbe1-e49a88b2541a', 'Demo App', 'Demo App description', '2f7cc63df4b1da7532756f44345758da');

61
charts/nebulous-cloud-fog-service-broker/templates/deployment-postgres.yaml Normal file
View File

@ -0,0 +1,61 @@
{{ if .Values.postgresql.enabled }}
apiVersion: apps/v1
kind: Deployment
metadata:
name: {{ include "nebulous-cloud-fog-service-broker.fullname" . }}-postgresql
labels:
{{- include "nebulous-cloud-fog-service-broker.labels" . | nindent 4 }}
spec:
selector:
matchLabels:
{{- include "nebulous-cloud-fog-service-broker.selectorLabels" . | nindent 6 }}
template:
metadata:
labels:
{{- include "nebulous-cloud-fog-service-broker.selectorLabels" . | nindent 8 }}
spec:
volumes:
- name: postgres-data
persistentVolumeClaim:
claimName: {{ .Values.postgresql.volumeMounts.data.claimName }}
- name: init-script
configMap:
name: {{ .Values.postgresql.volumeMounts.initScript.configMapName }}
containers:
- name: postgresql
image: "{{ .Values.postgresql.image }}"
ports:
- name: postgresql
containerPort: {{ .Values.postgresql.port }}
protocol: TCP
env:
- name: POSTGRES_USER
value: "{{ .Values.postgresql.user }}"
- name: POSTGRES_PASSWORD
value: "{{ .Values.postgresql.password }}"
- name: POSTGRES_DB
value: "{{ .Values.postgresql.dbName }}"
volumeMounts:
- name: postgres-data
mountPath: /var/lib/postgresql/data/
- name: init-script
mountPath: /docker-entrypoint-initdb.d
---
apiVersion: v1
kind: Service
metadata:
name: {{ include "nebulous-cloud-fog-service-broker.fullname" . }}-postgresql
labels:
{{- include "nebulous-cloud-fog-service-broker.labels" . | nindent 4 }}
spec:
type: ClusterIP
ports:
- port: {{ .Values.postgresql.port }}
targetPort: postgresql
protocol: TCP
name: postgresql
selector:
{{- include "nebulous-cloud-fog-service-broker.selectorLabels" . | nindent 4 }}
{{ end }}

29
charts/nebulous-cloud-fog-service-broker/templates/deployment.yaml
View File

@ -35,18 +35,29 @@ spec:
imagePullPolicy: {{ .Values.image.pullPolicy }}
ports:
- name: http
containerPort: 8080
containerPort: 8001
protocol: TCP
livenessProbe:
httpGet:
path: /
port: http
readinessProbe:
httpGet:
path: /
port: http
resources:
{{- toYaml .Values.resources | nindent 12 }}
env:
- name: NEBULOUS_BROKER_URL
value: "{{ .Values.customEnv.NEBULOUS_BROKER_URL }}"
- name: NEBULOUS_BROKER_PORT
value: "{{ .Values.customEnv.NEBULOUS_BROKER_PORT }}"
- name: NEBULOUS_BROKER_USERNAME
value: "{{ .Values.customEnv.NEBULOUS_BROKER_USERNAME }}"
- name: NEBULOUS_BROKER_PASSWORD
value: "{{ .Values.customEnv.NEBULOUS_BROKER_PASSWORD }}"
- name: POSTGRES_DB_HOST
value: "{{ .Values.customEnv.POSTGRES_DB_HOST }}"
- name: POSTGRES_DB_NAME
value: "{{ .Values.customEnv.POSTGRES_DB_NAME }}"
- name: POSTGRES_DB_PORT
value: "{{ .Values.customEnv.POSTGRES_DB_PORT }}"
- name: POSTGRES_DB_USER
value: "{{ .Values.customEnv.POSTGRES_DB_USER }}"
- name: POSTGRES_DB_PASS
value: "{{ .Values.customEnv.POSTGRES_DB_PASS }}"
{{- with .Values.nodeSelector }}
nodeSelector:
{{- toYaml . | nindent 8 }}

10
charts/nebulous-cloud-fog-service-broker/templates/pvc-postgresql.yaml Normal file
View File

@ -0,0 +1,10 @@
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: postgresql-pvc
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 1Gi

26
charts/nebulous-cloud-fog-service-broker/values.yaml
View File

@ -5,7 +5,7 @@
replicaCount: 1
image:
repository: "quay.io/nebulous/cloud-fog-service-broker-java-spring-boot-demo"
repository: "quay.io/nebulous/cloud-fog-service-broker-backend"
pullPolicy: IfNotPresent
# Overrides the image tag whose default is the chart appVersion.
tag: ""
@ -80,3 +80,27 @@ nodeSelector: {}
tolerations: []
affinity: {}
customEnv:
NEBULOUS_BROKER_URL: "nebulous-activemq"
NEBULOUS_BROKER_PORT: "61616"
NEBULOUS_BROKER_USERNAME: "admin"
NEBULOUS_BROKER_PASSWORD: "admin"
POSTGRES_DB_HOST: "localhost"
POSTGRES_DB_NAME: "fog_broker"
POSTGRES_DB_PORT: "5432"
POSTGRES_DB_USER: "dbuser"
POSTGRES_DB_PASS: "pass123"
postgresql:
enabled: true
image: "docker.io/postgres:16"
user: "dbuser"
password: "pass123"
dbName: "fog_broker"
port: 5432
volumeMounts:
data:
claimName: "postgresql-pvc"
initScript:
configMapName: "db-init-script"

41
docker-compose.yml Normal file
View File

@ -0,0 +1,41 @@
version: '3.0'
services:
backend:
build:
context: ./cfsb-backend
dockerfile: Dockerfile
ports:
- "8001:8001"
env_file:
- ./cfsb-backend/.env.prod
depends_on:
- db
networks:
cfsb-network:
db:
image: postgres:16
ports:
- "5432:5432"
environment:
- POSTGRES_USER=dbuser
- POSTGRES_PASSWORD=pass123
- POSTGRES_DB=fog_broker
volumes:
- postgres_data:/var/lib/postgresql/data/
- ./cfsb-backend/db/db_script.sql:/docker-entrypoint-initdb.d/db_script.sql
networks:
cfsb-network:
frontend:
build:
context: ./cfsb-frontend
dockerfile: Dockerfile
ports:
- "8080:80"
networks:
cfsb-network:
networks:
cfsb-network:
volumes:
postgres_data:

33
java-spring-boot-demo/.gitignore vendored
View File

@ -1,33 +0,0 @@
HELP.md
target/
!.mvn/wrapper/maven-wrapper.jar
!**/src/main/**/target/
!**/src/test/**/target/
### STS ###
.apt_generated
.classpath
.factorypath
.project
.settings
.springBeans
.sts4-cache
### IntelliJ IDEA ###
.idea
*.iws
*.iml
*.ipr
### NetBeans ###
/nbproject/private/
/nbbuild/
/dist/
/nbdist/
/.nb-gradle/
build/
!**/src/main/**/build/
!**/src/test/**/build/
### VS Code ###
.vscode/

15
java-spring-boot-demo/Dockerfile
View File

@ -1,15 +0,0 @@
#
# Build stage
#
FROM docker.io/library/maven:3.9.2-eclipse-temurin-17 AS build
COPY src /home/app/src
COPY pom.xml /home/app
RUN mvn -f /home/app/pom.xml clean package
#
# Package stage
#
FROM docker.io/library/eclipse-temurin:17-jre
COPY --from=build /home/app/target/demo-0.0.1-SNAPSHOT.jar /usr/local/lib/demo.jar
EXPOSE 8080
ENTRYPOINT ["java","-jar","/usr/local/lib/demo.jar"]

42
java-spring-boot-demo/pom.xml
View File

@ -1,42 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>3.1.0</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<groupId>com.example</groupId>
<artifactId>demo</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>demo</name>
<description>Demo project for Spring Boot</description>
<properties>
<java.version>17</java.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>

13
java-spring-boot-demo/src/main/java/com/example/demo/DemoApplication.java
View File

@ -1,13 +0,0 @@
package com.example.demo;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class DemoApplication {
public static void main(String[] args) {
SpringApplication.run(DemoApplication.class, args);
}
}

14
java-spring-boot-demo/src/main/java/com/example/demo/DemoController.java
View File

@ -1,14 +0,0 @@
package com.example.demo;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
@RestController
public class DemoController {
@RequestMapping("/")
public Object root() {
return null;
}
}

0
java-spring-boot-demo/src/main/resources/application.properties
View File

13
java-spring-boot-demo/src/test/java/com/example/demo/DemoApplicationTests.java
View File

@ -1,13 +0,0 @@
package com.example.demo;
import org.junit.jupiter.api.Test;
import org.springframework.boot.test.context.SpringBootTest;
@SpringBootTest
class DemoApplicationTests {
@Test
void contextLoads() {
}
}

24
zuul.d/jobs.yaml
View File

@ -6,17 +6,24 @@
soft: false
provides:
- nebulous-cloud-fog-service-broker-container-images
description: Build the container images.
description: Build the container images for both the backend and frontend.
files: &image_files
- ^java-spring-boot-demo/
- ^cfsb-backend/
- ^cfsb-frontend/
vars: &image_vars
promote_container_image_job: nebulous-cloud-fog-service-broker-upload-container-images
container_images:
- context: java-spring-boot-demo
- context: cfsb-backend
registry: quay.io
repository: quay.io/nebulous/cloud-fog-service-broker-java-spring-boot-demo
repository: quay.io/nebulous/cloud-fog-service-broker-backend
namespace: nebulous
repo_shortname: cloud-fog-service-broker-java-spring-boot-demo
repo_shortname: cloud-fog-service-broker
repo_description: ""
- context: cfsb-frontend
registry: quay.io
repository: quay.io/nebulous/cloud-fog-service-broker-frontend
namespace: nebulous
repo_shortname: cloud-fog-service-broker
repo_description: ""
- job:
@ -27,14 +34,14 @@
soft: false
provides:
- nebulous-cloud-fog-service-broker-container-images
description: Build and upload the container images.
description: Build and upload both the backend and frontend container images.
files: *image_files
vars: *image_vars
- job:
name: nebulous-cloud-fog-service-broker-promote-container-images
parent: nebulous-promote-container-images
description: Promote previously uploaded container images.
description: Promote previously uploaded backend and frontend container images.
files: *image_files
vars: *image_vars
@ -44,7 +51,8 @@
description: Run Hadolint on Dockerfile(s).
vars:
dockerfiles:
- java-spring-boot-demo/Dockerfile
- cfsb-backend/Dockerfile
- cfsb-frontend/Dockerfile
- job:
name: nebulous-cloud-fog-service-broker-helm-lint