Cloud Scheduling using Multi-Objective League Championship Algorithm

Project Overview

This project enables testing and analysis of cloud scheduling algorithms, with primary focus on:

• MO-LCA (Multi-Objective League Championship Algorithm)
• Comparative analysis with other algorithms (ACO, PSO, Round Robin)
• Performance evaluation in simulated cloud environments

Key Features

• Multi-objective cloud scheduling optimization using MO-LCA
• Comparative analysis of algorithms (ACO, PSO, Round Robin)
• Modular architecture with orchestration for easy integration
• Interactive web interface for configuration and visualization
• Plugin architecture for the algorithm module for easy algorithms integration
• Cloud simulation environment using CloudSim-Plus framework

Requirements

• Python: 3.7+
• Node.js: 20.x+
• Java: JDK 17+ (for simulator)
• Maven: 3.6+ (for Java build)
• npm: 10.x+

1. Setup using Conda

git clone https://github.com/ghifarhaidar/cloud-scheduling-using-lca.git
cd cloud-scheduling-using-lca/

Create and activate a Conda environment

conda create -n myenv -y
conda init
conda activate myenv

Install required packages

conda install maven nodejs numpy -y

Install dependencies

cd backend/
npm install
cd ../frontend/
npm install
cd ..

Build the Java simulator

python3 run.py --job 3

2. Setup without Conda (system-wide)

git clone https://github.com/ghifarhaidar/cloud-scheduling-using-lca.git
cd cloud-scheduling-using-lca/

[Optional] Create and activate a Python virtual environment

python3 -m venv .venv
source .venv/bin/activate

Install required system-level tools

(Assumes you're on Ubuntu or Debian)

sudo apt-get update
sudo apt-get install -y maven nodejs npm python3-pip

Upgrade pip and install Python deps

pip install --upgrade pip
pip install numpy

Install backend dependencies

cd backend/
npm install
cd ..

Install frontend dependencies

cd frontend/
npm install
cd ..

Build the Java simulator and run the project

python3 run.py --job 3

save your env variable in both the 'frontend/' and 'backend/'

then run npm run start in both backend and frontend folders

Integration Tests

pytest tests/test_full_workflow.py

Project Architecture

Core Components

1. Algorithms Module
Contains implementations of scheduling algorithms:

• /lca/:
  • MO_LCA.py: Multi-Objective League Championship Algorithm
  • makespan_LCA.py, cost_LCA.py (single-objective variants)
• /algorithms/:
  • ACO.py: Ant Colony Optimization implementation
  • PSO.py: Particle Swarm Optimization variant
  • Round_Robin.py: Traditional round-robin baseline

2. CloudSim-Plus Integration (/src/main/java/)

• Custom Java classes extending CloudSim-Plus:
  • MyDatacenterBroker.java: Modified broker for custom scheduling
  • MyVmCost.java: Custom VM cost modeling
  • Simulation.java: Core simulation runner

3. Backend Service (/backend/)

• Node.js API features:
  • runOrchestrator.js: Invokes The main Orchestrator that runs algorithm and simulation execution
  • resultProcessor.js: Handles simulation output
  • REST API routes in api.js for frontend communication

4. Frontend Interface (/frontend/)

• React-based UI with:
  • Configuration setup Page (SetConfigPage.jsx)
  • Fitness evolution visualization (FitnessPage.jsx)
  • Results visualization (ResultsSection.jsx)
  • Pareto front visualization (resultsPage.jsx)

Key Workflows

Simulation Pipeline:

1. Configuration Phase

   • User sets up MO-LCA parameters (population size, iterations, etc.)
   • Configures simulation environment (VM counts, cloudlets, etc.)

2. Execution Phase

   • Frontend sends configuration to Backend API
   • Backend orchestrates:
     a. Runs MO-LCA and other desired scheduling algorithm
     b. Triggers Java simulator
     c. Processes CloudSim-Plus output metrics

3. Visualization Phase

   • Backend returns processed results to Frontend
   • Interactive React components display:
     • Scheduling performance metrics
     • Comparative algorithm analysis
     • Pareto fronts for multi-objective optimization
     • Fitness evolution

Plugin Architecture:

• New algorithms can be added by:
  1. Adding implementation in /algorithms/
  2. Updating configs/all_algorithms.json
  3. No core changes required

Configuration System

• JSON configs in /configs/ control:
  • Algorithm parameters
  • Cloud infrastructure specs

detailed files architecture:

.
├── algorithms
│   ├── ACO.py
│   ├── main.py
│   ├── PSO.py
│   └── Round_Robin.py
├── backend
│   ├── config
│   │   ├── config.js
│   │   └── corsOptions.js
│   ├── example.env
│   ├── middleware
│   │   ├── asyncHandler.js
│   │   ├── errorHandler.js
│   │   └── logging.js
│   ├── package.json
│   ├── package-lock.json
│   ├── routes
│   │   └── api.js
│   ├── server.js
│   └── utils
│       ├── fileHandlers.js
│       ├── resultProcessor.js
│       ├── runExperiments.js
│       └── runOrchestrator.js
├── clean_and_update.sh
├── configs
│   └── all_algorithms.json
├── frontend
│   ├── eslint.config.js
│   ├── example.env.local
│   ├── index.html
│   ├── package.json
│   ├── package-lock.json
│   ├── public
│   │   └── icon.svg
│   ├── src
│   │   ├── App.css
│   │   ├── App.jsx
│   │   ├── assets
│   │   │   └── react.svg
│   │   ├── components
│   │   │   ├── AlgorithmCard.jsx
│   │   │   ├── AlgorithmConfiguration.jsx
│   │   │   ├── CustomConfigSection.jsx
│   │   │   ├── loadingError.jsx
│   │   │   ├── loading.jsx
│   │   │   ├── NavBar.jsx
│   │   │   ├── ResultsSection.jsx
│   │   │   ├── SelectableAlgorithmCard.jsx
│   │   │   └── SimulationConfiguration.jsx
│   │   ├── index.css
│   │   ├── main.jsx
│   │   ├── pages
│   │   │   ├── EditConfigPage.jsx
│   │   │   ├── FitnessPage.jsx
│   │   │   ├── HomePage.jsx
│   │   │   ├── ResultsPage.jsx
│   │   │   ├── RunPage.jsx
│   │   │   └── SetConfigPage.jsx
│   │   ├── styles
│   │   │   ├── buttons.css
│   │   │   ├── cards.css
│   │   │   ├── navbar.css
│   │   │   └── resultsPage.css
│   │   └── utils
│   │       ├── api.js
│   │       ├── fitnessPageUtil.js
│   │       ├── resultPreprocessing.js
│   │       └── setConfigPageUtil.js
│   └── vite.config.js
├── .github
│   └── workflows
│       └── integration.yml
├── .gitignore
├── lca
│   ├── config.py
│   ├── cost_config.py
│   ├── cost_LCA.py
│   ├── dev.py
│   ├── main.py
│   ├── makespan_LCA.py
│   ├── MO_LCA.py
│   ├── Non_Vectorized_MO_LCA.py
│   ├── util.py
│   └── vectorized_dev.py
├── pom.xml
├── README.md
├── run.py
├── src
│   └── main
│       └── java
│           ├── brokers
│           │   └── MyDatacenterBroker.java
│           ├── org
│           │   └── simulations
│           │       └── Simulation.java
│           ├── utils
│           │   └── commons.java
│           └── vms
│               └── MyVmCost.java
└── tests
    └── test_full_workflow.py

Documentation

Project documentation is available in /.docs/ directory: