Fairness-Aware Computation Offloading for Mobile Edge Computing With Energy Harvesting

The "Fairness-Aware Computation Offloading for Mobile Edge Computing with Energy Harvesting" system aims to optimize the resource allocation in Mobile Edge Computing (MEC) environments while addressing energy constraints and fairness concerns. The system, built with a robust backend using Java with Spring Boot and MySQL database, and a frontend developed in HTML, CSS, and ReactJS, supports both admin and user roles. The admin manages user accounts, experiments, and logs, while users can register, log in, create and run experiments, and view results. The system employs a Fairness-Aware Computation Offloading (FACOO) algorithm, which leverages the Lyapunov approach and Sequential Least Squares Quadratic Programming (SLSQP) for efficient computation offloading, considering signal-to-interference-plus-noise ratio (SINR) limitations and energy harvesting. The primary objective is to ensure fairness and enhance throughput, while minimizing energy consumption. Through simulations, the proposed system demonstrates significant improvements in fairness and energy efficiency, making it a viable solution for resource-constrained MEC systems.

Keywords: Mobile Edge Computing, Computation Offloading, Energy Harvesting, Fairness, SINR, Lyapunov Optimization, SLSQP, Algorithm, Resource Allocation, MEC Systems.