Adaptive delay-energy balanced partial offloading strategy in Mobile Edge Computing networks

作     者：Shumei Liu Yao Yu Lei Guo Phee Lep Yeoh Branka Vucetic Yonghui Li Shumei Liu;Yao Yu;Lei Guo;Phee Lep Yeoh;Branka Vucetic;Yonghui Li

作者机构：School of Computer Science and EngineeringNortheastern UniversityShenyang110819China Key Laboratory of Intelligent Computing in Medical ImageMinistry of EducationNortheastern UniversityShenyang110819China School of Communication and Information EngineeringChongqing University of Posts and TelecommunicationsChongqing400065China School of Electrical and Information EngineeringUniversity of SydneySydneyNSW2006Australia 

出 版 物：《Digital Communications and Networks》 (数字通信与网络（英文版）)

年 卷 期：2023年第9卷第6期

页      面：1310-1318页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：This work was supported in part by the National Natural Science Foundation of China under Grant 62171113 and 61941113 in part by the Fundamental Research Funds for the Central Universities under Grant N2116003 and N2116011 

主　　题：Mobile edge computing(MEC) Delay Energy consumption Dynamic balance Partial computation offloading 

摘      要：Mobile Edge Computing(MEC)-based computation offloading is a promising application paradigm for serving large numbers of users with various delay and energy *** this paper,we propose a flexible MECbased requirement-adaptive partial offloading model to accommodate each user s specific preference regarding delay and energy *** address the dimensional differences between time and energy,we introduce two normalized parameters and then derive the computational overhead of processing *** from existing works,this paper considers practical variations in the user request patterns,and exploits a flexible partial offloading mode to minimize computation overheads subject to tolerable delay,task workload and power *** the resulting problem is non-convex,we decouple it into two convex subproblems and present an iterative algorithm to obtain a feasible offloading *** experiments show that our proposed scheme achieves a significant improvement in computation overheads compared with existing schemes.