Resource allocation scheme based on gray wolf optimization algorithm in mobile edge computing

Abstract

Aiming at the problem of server resource allocation in Mobile Edge Computing (MEC) task migration, considering the limitation and heterogeneity of server resources, a resource allocation model aiming at minimizing the system server energy consumption is constructed. And proposed a Dynamic Weighted Grey Wolf Optimization (DWGWO) algorithm to solve the optimal resource allocation scheme. The initialization, convergence factor and update strategy of Gray Wolf Optimization (GWO) algorithm are improved to improve the convergence performance of the algorithm and avoid the algorithm falling into local optimum. Simulation results show that DWGWO algorithm can find the optimal solution of resource allocation scheme quickly, reduce the energy consumption of server operation, and is superior to Random strategy, Genetic algorithm and GWO in convergence and stability.