Computer Science ›› 2021, Vol. 48 ›› Issue (1): 72-80.doi: 10.11896/jsjkx.200800088

Special Issue: Intelligent Edge Computing

• Intelligent Edge Computing • Previous Articles     Next Articles

Multi-edge Collaborative Computing Unloading Scheme Based on Genetic Algorithm

GAO Ji-xu, WANG Jun   

  1. School of Communication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210000,China
  • Received:2020-08-16 Revised:2020-10-18 Online:2021-01-15 Published:2021-01-15
  • About author:GAO Ji-xu,born in 1996,postgraduate.His main research interests include mobile edge computing and IoT.
    WANG Jun,born in 1975,Ph.D,asso-ciate professor.Her main research inte-rests include network architecture of IoT and wireless sensor networks.

Abstract: As a supplement to cloud computing,edge computing can ensure that the calculation delay meets system requirements when processing computing tasks generated by lOT equipment.Aiming at the problem of insufficient utilization of the remote edge cloud due to the empty window period of the computing task in the traditional offloading scenario,a genetic algorithm-based multi-edge and cloud collaborative computing offloading model (Genetic Algorithm-based Multi-edge Collaborative Computing Offloading Model,GAMCCOM) is proposed.This computing offloading solution combines local edge and remote edge to perform task offloading and uses a genetic algorithm to get the minimum system cost under consideration of both delay and energy consumption at the same time.The results of simulation experiments show that when considering the time delay consumption and energy consumption of the unloading system,the overall cost of this scheme is reduced by 23% compared with the basic three-layer unloading scheme.In the case of considering time delay consumption and energy consumption respectively,the system cost can still be reduced by 17% and 15% respectively.Therefore,the GAMCCOM offloading method can effectively reduce the system cost for different offloading targets of edge computing.

Key words: Collaborative unloading, Computing unloading, Edge computing, Genetic algorithm, Internet of things

CLC Number: 

  • TP393
[1] XIE R C,LIAN X F,JIA Q M,et al.Overview of mobile edge computing offloading technology [J].Journal on Communications,2018,39(11):138-155.
[2] YUW,HE L F.A Survey on the Edge Computing for the Internet of Things [J].IEEE Access,2017,6(8):6900-6919.
[3] MARTINA M,ALEKSANDAR A,LVANA P Z,et al.EdgeComputing Architecture for Mobile Crowdsensing [J].IEEE Access,2018,6(5):10662-10674.
[4] MAO Y Y,YOU C S,ZHANG J,et al.A Survey on Mobile Edge Computing:The Communication Perspective[J].IEEE Communications Surveys & Tutorials,2017,19(4):2322-2358.
[5] PAN J L,JAMES M.Future Edge Cloud and Edge Computing for Internet of Things Applications[J].IEEE Internet of Things Journal,2018,5(1):439-449.
[6] LIU J,MAO Y Y,ZHANG J,et al.Delay-optimal computation task scheduling for mobile-edge computing systems[J].IEEE International Symposium on Information Theory (ISIT),2016,1(4):1451-1455.
[7] YOU C S,HUANG K B.Exploiting Non-Causal CPU-State Information for Energy-Efficient Mobile Cooperative Computing[J].IEEE Transactions on Wireless Communications,2018,17(6):4104-4117.
[8] CHEN L X,ZHOU S,XU J.Computation Peer Offloading for Energy-Constrained Mobile Edge Computing in Small-Cell Networks[J].IEEE/ACM Transactions on Networking,2018,26(4):1619-1932.
[9] ZHOU J S,TIAN D X,WANG Y al.Reliability-Optimal Cooperative Communication and Computing in Connected Vehicle Systems[J].IEEE Transactions on Mobile Computing,2020,19(5):1216-1232.
[10] CAO X W,WANG F,XU J,et al.Joint computation and communication cooperation for energy-efficient mobile edge computing[J].IEEE Internet of Things Journal,2019,6(3):4188-4200.
[11] DAI Y Y,XU D,MAHARJAN S,et al.Joint Load Balancingand Offloading in Vehicular Edge Computing and Networks[J].IEEE Internet of Things Journal,2019,6(3):4377-4387.
[12] ZOU S.Research and Implementation of Computing Offloading and Image Cache Method in Edge Computing Platform[D].Beijing:Beijing University of Posts and Telecommunications,2019.
[13] WU Z K,JIANG L Y,MU Y R.Research on application unloading algorithm with multi edge nodes [J].Journal of Nanjing University of Posts and Telecommunications:Natural Science Edition,2019,39(4):96-102.
[14] CHEN B,QUAN G R.NP-Hard Problems of Learning from Examples[C]//2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery.2008,2:182-186.
[15] DEB K,PRATAP A,AGARWAL S,et al.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
[16] LE G X,DAI Y S,YANG X H,et al.Modeling of trusted colla-borative service strategy in edge computing [J].Computer Research and Development,2020,57(5):1080-1102.
[17] SONG Y Z,STEPHEN S Y,YU R Z,et al.An Approach to QoS-based Task Distribution in Edge Computing Networks for IoT Applications[J].IEEE International Conference on Edge Computing (EDGE),2017,13(5):32-39.
[18] GUO H Z,LIU J J.Collaborative Computation Offloading for Multiaccess Edge Computing Over Fiber-Wireless Networks[J].IEEE Transactions on Vehicular Technology,2018,67(5):4514-4526.
[19] GERUTTI G,PRASAD R,BRUTTI A,et al.Compact Recurrent Neural Networks for Acoustic Event Detection on Low-Energy Low-Complexity Platforms[J].IEEE Journal of Selected Topics in Signal Processing,2020,14(4):654-664.
[20] BADRI H,BAHREINI T,GROSU D,et al.Energy-Aware Application Placement in Mobile Edge Computing:A Stochastic Optimization Approach[J].IEEE Transactions on Parallel and Distributed Systems,2020,31(4):909-922.
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