Optimization Scheme of Single-Objective Task Offloading with Multi-user Participation in Cloud-Edge-End Environment
Xiao Wang, Xiaofei Xing, Peiqiang Li, Shaohong Zhang · 2022
With the development of mobile edge computing (MEC), users can choose to offload tasks to the network edge for computing, but it also causes problems of energy consumption and delay. In this paper, we study a three-layer optimized task offloading framework based on single Computing Access Point (CAP) and independent cloud, where several users at the user end can choose to offload their own tasks to the edge end and the cloud end for computing. The mobile user at the user end forwards the task to the edge end through the base station (BS) or delivers the task to the cloud through wireless transmission, and both cannot be selected at the same time. Then, we optimize the proposed task offloading based on particle swarm optimization (PSO) algorithm and derive the optimal offloading strategy to reduce energy consumption and delay. Through simulation, the number of users and bandwidth are changed, and the advantages of the proposed optimization scheme in terms of energy consumption and delay compared with the all-local, all-edge and all-cloud are finally verified.