Hybrid Metaheuristic Based Resource Allocation Approach in SDN-Based Edge Computing Environment
Ajay Nain, Sophiya Sheikh, Rohit Malik, Sheikh Umar Mushtaq · 2023
The demand for an effective controller to guarantee optimal resource utilisation in edge computing (EC) has increased due to the exponential growth of the Internet use and the dispersed nature of computing resources in edge devices. In this study, we focus on one particular aspect of edge computing: the issue of allocating resources, to minimize time delays while conserving the battery power of user devices. For this purpose, we introduced a novel hybrid metaheuristic specifically designed to optimize total time and energy consumption in a hybrid cloud computing environment. The proposed algorithm leverages the strengths of both Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) techniques. To evaluate the effectiveness of our approach, we conducted a comprehensive comparison between the Hybrid PSO-GWO, PSO, and GWO methods. Through simulations and experiments, we examined their performance in terms of time delays and energy consumption. The results demonstrate that the Hybrid PSO-GWO algorithm outperforms both PSO and GWO, proving its efficacy in achieving more efficient and effective resource allocation in wireless edge computing scenarios.