Resource Allocation and Task Offloading Strategy Base on Hybrid Simulated Annealing-Binary Particle Swarm Optimization in Cloud-Edge Collaborative System

Abstract

Taking the latency, energy consumption and computing resource cost into consideration comprehensively, we construct a single-cell, multi-user cloud-edge collaborative system model and decompose the optimization problem of task offloading and resource allocation aiming at minimizing the total user overhead into three sub-problems: computing resource allocation, uplink power allocation and task offloading. Computing resource and uplink power allocation are optimized by using convex optimization technique and bisection method respectively. To optimize task offloading, we propose a simulated annealing-binary particle swarm optimization algorithm(SA-BPSO). Simulation results show that SA-BPSO can better reduce the total user overhead compared with the other three schemes and ensure user quality of service quality.