Energy-Aware and Mobility-Driven Computation Offloading in MEC

作     者：Chen, Liqiong Liu, Yingda Lu, Yijun Sun, Huaiying 

作者机构：Shanghai Inst Technol Dept Comp Sci & Informat Engn Shanghai Peoples R China 

出 版 物：《JOURNAL OF GRID COMPUTING》 (网格计算杂志)

年 卷 期：2023年第21卷第2期

页      面：1-18页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Capacity building project of local universities Science and Technology Commission of Shanghai Municipality Shanghai Rising-Star Program (Sailing Program) [22YF1448100] Scientific Research Starting Foundation of Shanghai Institute of Technology Development Fund for young and middle-aged scientific and technological talents of Shanghai Institute of Technology [ZQ2021-19] Development of Science and Technology of Shanghai Institute of Technology [KJFZ2021-177, KJFZ2021-176] 

主　　题：Edge computing Computation offloading Workflow K-Means Energy constraint 

摘      要：Heuristic algorithms are widely used in Mobile Edge Computing(MEC) to improve the performance of mobile devices. However, the time complexity of the heuristic algorithm is high, and it is complex to optimize under constraints. Therefore, we proposed Multi-User Energy Constraint Time Optimization Algorithm(MU-ECTOA) for workflow makespan optimization under energy constraints. MU-ECTOA includes three stages: cluster analysis, evaluation of performance, and workflow offloading. In the first stage, the workflow tasks are classified according to their characteristics;In the second stage, the subtask groups are obtained, and the evaluation results of each subtask group are obtained. In the third stage, the optimal subtask group is selected for offloading and then updated the ready time of edge nodes. Extensive experiments have been conducted, the ACO&GA, Max-Min, Particle Swarm Optimization(PSO), GA-DPSO, and SFLA are taken as the compared methods. The results of MU-ECTOA performs better in aspects in completion time, load balancing, and successful offloading rate compared with other methods. By comparing the results of algorithms, the makespans of the algorithms are close, but the algorithm complexity and load balancing of MU-ECTOA are much better;The time complexity of the MU-ECTOA algorithm is close to the Max-Min s, but MU-ECTOA performs better in makespan and algorithm reliability.