Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (3): 280-288.doi: 10.11896/jsjkx.221100250

• Computer Network • Previous Articles     Next Articles

Multi-objective Optimization of D2D Collaborative MEC Based on Improved NSGA-III

WANG Zhihong1, WANG Gaocai1, ZHAO Qifei2   

  1. 1 School of Computer and Electronic Information,Guangxi University,Nanning 530004,China
    2 School of Electrical Engineering,Guangxi University,Nanning 530004,China
  • Received:2022-11-29 Revised:2023-01-11 Online:2024-03-15 Published:2024-03-13
  • About author:WANG Zhihong,born in 1999,postgraduate.His main research interests include computer network and mobile edge computing.WANG Gaocai,born in 1976,Ph.D,professor,doctoral supervisor.His main research interests include computer network,performance evaluation and network security.
  • Supported by:
    National Natural Science Foundation of China(62062007).

PDF (PC)

1102

Abstract: In the current mobile edge computing(MEC),since tasks are directly uploaded to the MEC server for execution,there are problems such as high computing pressure on the edge server and insufficient utilization of resources on idle mobile devices.Using idle devices in the edge network for collaborative computing can realize rational utilization of user's idle resources and enhance the computing capacity of MEC.Therefore,a device-to- device(D2D) collaborative MEC for partial offloading(DCM-PO) is proposed.In this model,in addition to local computing and MEC server computing,part of the tasks can be uploaded to idle D2D devices for auxiliary computing.First,a multi-objective optimization problem is established to minimize the delay,energy consumption and cost of the edge network.Then,the non-dominated sorting genetic algorithm III(NSGA-III) is improved in the aspects of multi-chromosome mixed coding,adaptive crossover rate and mutation rate,so that it is suitable for solving the multi-objective optimization problem in the DCM-PO.Finally,simulation results show that,compared with the baseline MEC,the DCM-PO has advantages in several performance indicators.

Key words: Mobile edge computing, Device-to-Device, Task offloading, Multi-objective optimization, NSGA-III

CLC Number: 

  • TP301
[1]ABBAS N,ZHANG Y,TAHERKORDI A,et al.Mobile edgecomputing:a survey[J].IEEE Internet of Things Journal,2018,5(1):450-465.
[2]BANGERTER B,TALWAR S,AREFI R,et al.Networks and devices for the 5G era[J].IEEE Communications Magazine,2017,52(2):90-96.
[3]BUMGARNER J M,LAMBERT C T,HUSSEIN A A,et al.Smartwatch algorithm for automated detection of atrial fibrillation[J].Journal of the American College of Cardiology,2018,71(21):2381-2388.
[4]LIU B,LIU C,PENG M.Resource allocation for energy-efficient MEC in NOMA-enabled massive IoT networks[J].IEEE Journal on Selected Areas in Communications,2021,39(4):1015-1027.
[5]WANG Y C,ZHU H,HEI X H,et al.An energy saving based on task migration for mobile edge computing[J].Journal on Wireless Communications and Networking,2019(1):133.
[6]WANG F,XU J,WANG X,et al.Joint offloading and computing optimization in wireless powered mobile edge computing systems[J].IEEE Transactions on Wireless Communications,2018,17(3):1784-1797.
[7]LIU S M,YU Y,GUO L,et al.Adaptive delay-energy balanced partial offloading strategy in mobile edge computing networks[J/OL].https://doi.org/10.1016/j.dcan.2022.05.029.
[8]HE Y,REN J,YU G,et al.D2D communications meet mobileedge computing for enhanced computation capacity in cellular networks[J].IEEE Transactions on Wireless Communications,2019,18(3):1750-1763.
[9]CHEN X,ZHANG J S.When D2D meets cloud:hybrid mobile task offloadings in fog computing[C]//2017 IEEE International Conference on Communications.NJ:IEEE,2017:1-6.
[10]WANG H P,LIN Z P,LV T J.Energy and delay minimization of partial computing offloading for D2D-assisted MEC systems[C]//2021 IEEE Wireless Communications and Networking Conference.NJ:IEEE,2021:1-6.
[11]JIA Q M,XIE R C,TANG Q Q,et al.Energy-efficient computation offloading in 5G cellular networks with edge computing and D2D communications[J].IET Communications,2019,13(8):1122-1130.
[12]CAO X W,WANG F,XU J,et al.Joint computation and communication cooperation for mobile edge computing[J].IEEE Internet of Things Journal,2018,6(3):4188-4200.
[13]WANG C,QIN J H,YANG X X,et al.Energy-efficient offloa-ding policy in D2D underlay communication integrated with MEC service[C]//Proceedings of the 3rd International Confe-rence on High Performance Compilation,Computing and Communications.NY:ACM,2019:159-164.
[14]XIAO S R,LIU C B,LI K L,et al.System delay optimization for mobile edge computing[J].Future Generation Computer Systems,2020,109:17-28.
[15]LI G S,WANG J P,WU J H,et al.Data processing delay optimization in mobile edge computing[J].Wireless Communications and Mobile Computing,2018(5):1-9.
[16]SABUJ S R,ASIEDU D K P,LEE K J,et al.Delay optimization in mobile edge computing:cognitive UAV-assisted eMBB and mMTC services[J].IEEE Transactions on Cognitive Communications and Networking,2022,8(2):1019-1033.
[17]HABER E E,NGUYEN T M,EBRAHIMI D,et al.Computational cost and energy efficient task offloading in hierarchical edge clouds[C]//2018 IEEE 29th Annual International Symposium on Personal,Indoor and Mobile Radio Communications.NJ:IEEE,2018:1-6.
[18]LIU P C CHAUDHRY S R,HUANG T,et al.Multi-factorial energy aware resource management in edge networks[J].IEEE Transactions on Green Communications and Networking,2019,3(1):45-56.
[19]HU H,SONG W,WANG Q,et al.Energy efficiency and delay tradeoff in an MEC-enabled mobile IoT network[J].IEEE Internet of Things Journal,2022,9(17):15942-15956.
[20]LIU M,LIU Y.Price-based distributed offloading for mobileedge computing with computation capacity constraints[J].IEEE Wireless Communications Letters,2018,7(3):420-423.
[21]HAN D,CHEN W,FANG Y.A dynamic pricing strategy for vehicle assisted mobile edge computing systems[J].IEEE Wireless Communications Letters,2019,8(2):420-423.
[22]BAHREINI T,BADRI H,GROSU D.Mechanisms for resource allocation and pricing in mobile edge computing systems[J].IEEE Transactions on Parallel and Distributed Systems,2022,33(3):667-682.
[23]CHEN S,LI L,CHEN Z,et al.Dynamic pricing for smart mobile edge computing:a reinforcement learning approach[J].IEEE Wireless Communications Letters,2021,10(4):700-704.
[24]KAR U N,SANYAL D K.An overview of device-to-device communication in cellular networks[J].Information & Communications Technology Express,2018,4(4):203-208.
[25]CHAI R,LIN J L,CHEN M L,et al.Task execution cost minimization-based joint computation offloading and resource allocation for cellular D2D MEC systems[J].IEEE Systems Journal,2019,13(4):4110-4121.
[26]FENG Q,LI Q,QUAN W,et al.Overview of multiobjective particle swarm optimization algorithm[J].Chinese Journal of Engineering,2021,43(6):745-753.
[27]LIU J C,LI F,WANG H H,et al.Survey on evolutionary many-objective optimization algorithms[J].Control and Decision,2018,33(5):879-887.
[28]LIU Z Y,WANG Y J,SUN F L,et,al.Ensemble-assisted multi-objective optimization algorithm combining feature perturbation and allocation strategy[J].Computer Engineering,2022,48(6):115-123.
[29]PAN X T,WANG L P,ZHANG M H.Sparse multi-objective feature selection algorithm based on target vector guiding stra-tegy[J].Journal of Chinese Computer Systems.2023,44(10):2212-2220.
[30]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.
[31]ZHANG Q,LI H.MOEA/D:a multiobjective evolutionary algorithm based on decomposition[J].IEEE Transactions on Evolutionary Computation,2007,11(6):712-731.
[32]DEB K,JAIN H.An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach,part I:solving problems with box constraints[J].IEEE Transactions on Evolutionary Computation,2014,18(4):577-601.
[33]GENG H T,HAN W M,ZHOU S S,et al.MOEA/D algorithm based on new neighborhood updating strategy[J].Computer Science,2019,46(5):191-197.
[34]CHEN G C,YU J S.Enhanced particle swarm optimization algorithm and its application in soft sensing[J].Control and Decision,2005(4):377-381.
[35]BAI X B,JI X M,HU G.Improved particle swarm optimization method for needle roller bearings under multiple working conditions[J].Journal of Computer Aided Design and Graphics,2014,26(10):1900-1908.
[36]LI Y,XU G,YANG K,et al.Energy efficient relay selection and resource allocation in D2D-enabled mobile edge computing[J].IEEE Transactions on Vehicular Technology,2020,69(12):15800-15813.
[1] ZHU Wei, YANG Shibo, TENG Fan, HE Defeng. Study on Unmanned Vehicle Trajectory Planning in Unstructured Scenarios [J]. Computer Science, 2024, 51(4): 334-343.
[2] DING Shuang, CAO Muyu, HE Xin. Online Task Offloading Decision Algorithm for High-speed Vehicles [J]. Computer Science, 2024, 51(2): 286-292.
[3] ZHAO Xiaoyan, ZHAO Bin, ZHANG Junna, YUAN Peiyan. Study on Cache-oriented Dynamic Collaborative Task Migration Technology [J]. Computer Science, 2024, 51(2): 300-310.
[4] LIU Xingguang, ZHOU Li, ZHANG Xiaoying, CHEN Haitao, ZHAO Haitao, WEI Jibo. Edge Intelligent Sensing Based UAV Space Trajectory Planning Method [J]. Computer Science, 2023, 50(9): 311-317.
[5] LIN Xinyu, YAO Zewei, HU Shengxi, CHEN Zheyi, CHEN Xing. Task Offloading Algorithm Based on Federated Deep Reinforcement Learning for Internet of Vehicles [J]. Computer Science, 2023, 50(9): 347-356.
[6] ZHANG Naixin, CHEN Xiaorui, LI An, YANG Leyao, WU Huaming. Edge Offloading Framework for D2D-MEC Networks Based on Deep Reinforcement Learningand Wireless Charging Technology [J]. Computer Science, 2023, 50(8): 233-242.
[7] GENG Huantong, SONG Feifei, ZHOU Zhengli, XU Xiaohan. Improved NSGA-III Based on Kriging Model for Expensive Many-objective Optimization Problems [J]. Computer Science, 2023, 50(7): 194-206.
[8] CHEN Xuzhan, LIN Bing, CHEN Xing. Stackelberg Model Based Distributed Pricing and Computation Offloading in Mobile Edge Computing [J]. Computer Science, 2023, 50(7): 278-285.
[9] LEI Xuemei, LIU Li, WANG Qian. MEC Offloading Model Based on Linear Programming Relaxation [J]. Computer Science, 2023, 50(6A): 211200229-5.
[10] CHEN Che, ZHENG Yifeng, YANG Jingmin, YANG Liwei, ZHANG Wenjie. Dynamic Energy Optimization Strategy Based on Relay Selection and Queue Stability [J]. Computer Science, 2023, 50(6A): 220100082-8.
[11] GAO Lixue, CHEN Xin, YIN Bo. Task Offloading Strategy Based on Game Theory in 6G Overlapping Area [J]. Computer Science, 2023, 50(5): 302-312.
[12] PEI Cui, FAN Guisheng, YU Huiqun, YUE Yiming. Auction-based Edge Cloud Deadline-aware Task Offloading Strategy [J]. Computer Science, 2023, 50(4): 241-248.
[13] ZHONG Jialin, WU Yahui, DENG Su, ZHOU Haohao, MA Wubin. Multi-objective Federated Learning Evolutionary Algorithm Based on Improved NSGA-III [J]. Computer Science, 2023, 50(4): 333-342.
[14] CHEN Yipeng, YANG Zhe, GU Fei, ZHAO Lei. Resource Allocation Strategy Based on Game Theory in Mobile Edge Computing [J]. Computer Science, 2023, 50(2): 32-41.
[15] ZHENG Hongqiang, ZHANG Jianshan, CHEN Xing. Deployment Optimization and Computing Offloading of Space-Air-Ground Integrated Mobile Edge Computing System [J]. Computer Science, 2023, 50(2): 69-79.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.