移动边缘计算中任务卸载研究综述

doi:10.11896/jsjkx.220400161

摘要/Abstract

摘要： 随着物联网的普及以及5G等无线通信技术的发展,各类新型业务层出不穷,移动数据流量也呈指数级的增长趋势。为了保证服务质量,移动计算模式从传统的云计算转变为了移动边缘计算(MEC),移动边缘计算的主要特点是将网络资源“下沉”到网络边缘,以满足时延敏感型和计算密集型业务的需求,从而给用户提供更好的服务。而任务卸载是移动边缘计算的主要研究问题之一,文中对近几年移动边缘计算中的任务卸载研究现状进行了归纳和总结,首先,对MEC的基本概念、架构以及典型应用场景进行了介绍,然后阐述了任务卸载问题,分别从最小化时延、最小化能耗以及最小化时延和能耗的加权和3个方面分析和总结了业内的研究现状,最后从数据依赖性、用户移动性、资源公平性和信息安全性4个方面对未来的研究方向进行了展望。

关键词: 移动边缘计算, 边缘网络, 任务卸载, 任务延迟, 能量消耗

Abstract: With the popularity of the Internet of things and the development of wireless communication technologies such as 5G,various new services emerge one after another,and mobile data traffic is also growing exponentially.In order to guarantee the quality of service,the mobile computing model has changed from traditional cloud computing to mobile edge computing(MEC).The main feature of mobile edge computing is setting network resources at the edge of the network to meet the needs of delay-sensitive and computation-intensive tasks and provide users with better services.Task offloading is one of the main research problems in mobile edge computing.This paper summarizes the research status of task offloa-ding in MEC in recent years.Firstly,the basic concept,framework and typical application scenarios of MEC are introduced.Then it expounds the problem of task offloading,analyzes and summarizes the existing research results from minimum delay,minimum energy consumption and minimum weighted sum of delay and energy consumption respectively.Finally,the future research directions are prospected from four aspects:data dependency,user mobility,resource fairness and information security.

Key words: Mobile edge computing, Edge network, Task offloading, Task delay, Energy consumption

中图分类号:

TP393

高月红, 陈露. 移动边缘计算中任务卸载研究综述[J]. 计算机科学, 2022, 49(11A): 220400161-7. https://doi.org/10.11896/jsjkx.220400161

GAO Yue-hong, CHEN Lu. Survey of Research on Task Offloading in Mobile Edge Computing[J]. Computer Science, 2022, 49(11A): 220400161-7. https://doi.org/10.11896/jsjkx.220400161

参考文献

[1]HU Y C,PATEL M,SABELLA D,et al.Mobile edge computing—a key technology towards 5G[J].ETSI White Paper,2015,11(11):1-16.
[2]XIE R C,LIAN X F,JIA Q M,et al.Survey on computation offloading in mobile edge computing[J].Journal on Communications,2018,39(11):138-155.
[3]SHI W,CAO J,ZHANG Q,et al.Edge Computing:Vision and Challenges[J].IEEE Internet of Things Journal,2016,3(5):637-646.
[4]ZHAO S,ZHANG X,CAO P,et al.Design of Robust and Efficient Edge Server Placement and Server Scheduling Policies[C]//2021 IEEE/ACM 29th International Symposium on Qua-lity of Service(IWQOS).2021:1-7.
[5]LV J N,ZHANG J B,ZHANG Z F,et al.Survey of Mobile Edge Computing Offloading Strategies[J].Journal of Chinese Computer Systems,2020,41(9):1866-1877.
[6]SUN Q B,LIU J,LI S,et al.Internet of Things:Summarize on Concepts,Architecture and Key Technology Problem[J].Journal of Beijing University of Posts and Telecommunications,2010,33(3):1-9.
[7]NAVEEN S,KOUNTE M R.Key Technologies and challenges in IoT Edge Computing[C]//2019 Third International Confe-rence on I-SMAC(IoT in Social,Mobile,Analytics and Cloud)(I-SMAC).2019:61-65.
[8]XU Y N,CAI C,HOU Y L,et al.An Optimization Scheme of 5G Network Slicing Technology in Logistics Warehouse[J].Designing Techniques of Posts and Telecommunications,2021(4):84-87.
[9]ARTHURS P,GILLAM L,KRAUSE P,et al.A Taxonomy and Survey of Edge Cloud Computing for Intelligent Transportation Systems and Connected Vehicles[C]//IEEE Transactions on Intelligent Transportation Systems.2021.
[10]WANG K,WANG X,LIU X,et al.Task Offloading Strategy Based on Reinforcement Learning Computing in Edge Computing Architecture of Internet of Vehicles[C]//IEEE Access.2020:173779-173789.
[11]TONG X Y,FANG B Y,ZHANG Y Y.Internet of ThingsSmart Home Development Analysis [J].Mobile Communication,2010,34(9):16-20.
[12]GUPTA N,ANANTHARAJ K,SUBRAMANI K.Containe-rized Architecture for Edge Computing in Smart Home:A consistent architecture for model deployment[C]//2020 International Conference on Computer Communication and Informatics(ICCCI).2020:1-8.
[13]CHEN Y,YU L,OTA K,et al.Robust activity recognition for aging society[J].IEEE Journal of Biomedical and Health Informatics,2018,22(6):1754-1764.
[14]QIU Y,WANG C,QI K Y,et al.A Survey of Smart Health:System Design from the Cloud to the Edge[J].Journal of Computer Research and Development,2020,57(1):53-73.
[15]NI M X,ZHANG Q,TAN H Y,et al.Smart Healthcare:from IoT to Cloud Computing [J].Scientia Sinica Informationis,2013,43(4):515-528.
[16]XU J J,CHEN J.Development and applications of smart health care system based on internet of things[J].China Medical Devices,2017,32(10):118-121.
[17]SACCO A,ESPOSITO F,XMARCHETTO F,et al.On Edge Computing for Remote Pathology Consultations and Computations[C]//IEEE Journal of Biomedical and Health Informatics.2020:2523-2534.
[18]ZHANG Y L,LIANG Y Z,YIN M J,et al.Survey on the Methods of Computation Offloading in Mobile Edge Computing[J].Chinese Journal of Computers,2021,44(12):2406-2430.
[19]DONG J,FENG F.Efficient data offloading method for edge computing with privacy protection[J].Application Research of Computers,2021,38(7):2072-2076.
[20]ZHU Y K,LE G X,YANG X H,et al.Summary of Edge Computing Migration Research[J].Telecommunications Science,2019(4):74-94.
[21]MAO Y,YOU C,ZHANG J,et al.A Survey on Mobile Edge Computing:The Communication Perspective[C]// IEEE Communications Surveys & Tutorials.2017:2322-2358.
[22]SATYANARAYANAN M.Pervasive computing:vision andchallenges[J].IEEE Personal Communications,2001,8(4):10-17.
[23]BALAN R K,FLINN J.Cyber Foraging:Fifteen Years Later[J].IEEE Pervasive Computing,2017,16(3):24-30.
[24]WONG V,SCHOBER R,NG D,et al.Key Technologies for 5G Wireless Systems[D].Cambridge:Cambridge University Press,2017.
[25]DOU H,XU Z,JIANG X,et al.Mobile Edge Computing Based Task Offloading and Resource Allocation in Smart Grid[C]//2021 13th International Conference on Wireless Communications and Signal Processing(WCSP).2021:1-5.
[26]LU Y,ZHAO Z,GAO Q.A Distributed Offloading SchemeWith Flexible MEC Resource Scheduling[C]//2021 IEEE SmartWorld,Ubiquitous Intelligence & Computing,Advanced & Trusted Computing,Scalable Computing & Communications,Internet of People and Smart City Innovation(SmartWorld/SCALCOM/UIC/ATC/IOP/SCI).2021:320-327.
[27]LIU J,MAO Y,ZHANG J,et al.Delay-optimal computationtask scheduling for mobile-edge computing systems[C]//2016 IEEE International Symposium on Information Theory(ISIT).2016:1451-1455.
[28]YU Y,YAN Y,LI S,et al.Task Delay Minimization in Wireless Powered Mobile Edge Computing Networks:A Deep Reinforcement Learning Approach[C]//2021 13th International Confe-rence on Wireless Communications and Signal Processing(WCSP).2021:1-6.
[29]LI J.Maximizing User Service Satisfaction for Delay-Sensitive IoT Applications in Edge Computing[J].IEEE Transactions on Parallel and Distributed Systems,2022,33(5):1199-1212.
[30]NIU X.Workload Allocation Mechanism for Minimum Service Delay in Edge Computing-Based Power Internet of Things[J].IEEE Access,2019,7:83771-83784.
[31]ZHANG Y,DU P,WANG J,et al.Resource Scheduling for Delay Minimization in Multi-Server Cellular Edge Computing Systems[J].IEEE Access,2019,7:86265-86273,
[32]WANG H,LI R,FAN L,et al.Joint computation offloading and data caching with delay optimization in mobile-edge computing systems[C]//2017 9th International Conference on Wireless Communications and Signal Processing(WCSP).2017:1-6.
[33]CHEN X,ZHANG J,LIN B,et al.Energy-Efficient Offloading for DNN-Based Smart IoT Systems in Cloud-Edge Environments[J].IEEE Transactions on Parallel and Distributed Systems,2022,33(3):683-697.
[34]WU F,LENG S,MAHARJAN S,et al.Joint Power Control and Computation Offloading for Energy-efficient Mobile Edge Networks[J].IEEE Transactions on Wireless Communications,2022,21(6):4522-4534.
[35]GHOSH S,AGRAWAL D P.Prioritized computation offloading and resource optimization for networks with strict latency[C]//2021 IEEE 7th World Forum on Internet of Things(WF-IoT).2021:686-691.
[36]LI Q,WANG S,ZHOU A,et al.QoS Driven Task Offloading With Statistical Guarantee in Mobile Edge Computing[J].IEEE Transactions on Mobile Computing,2022,21(1):278-290.
[37]CHEN X,LIU G.Energy-Efficient Task Offloading and Re-source Allocation via Deep Reinforcement Learning for Augmented Reality in Mobile Edge Networks[J].IEEE Internet of Things Journal,2021,8(13):10843-10856.
[38]ZHAO T,ZHOU S,SONG L,et al.Energy-optimal and delay-bounded computation offloading in mobile edge computing with heterogeneous clouds[J].China Communications,2020,17(5):191-210.
[39]LABIDI W,SARKISS M,KAMOUN M.Joint multi-user re-source scheduling and computation offloading in small cell networks[C]//2015 IEEE 11th International Conference on Wireless and Mobile Computing,Networking and Communications(WiMob).2015:794-801.
[40]TAN L,KUANG Z F,ZHAO L,et al.Energy-Efficient Joint Task Offloading and Resource Allocation in OFDMA-based Collaborative Edge Computing[J].IEEE Transactions on Wireless Communications,2022,21(3):1960-1922.
[41]YOU C,HUANG K,CHAE H,et al.Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading[J].IEEE Transactions on Wireless Communications,2017,16(3):1397-1411.
[42]YU H,WANG Q,GUO S.Energy-Efficient Task Offloadingand Resource Scheduling for Mobile Edge Computing[C]//2018 IEEE International Conference on Networking,Architecture and Storage(NAS).2018:1-4.
[43]WU Z,YAN D.Deep reinforcement learning-based computation offloading for 5G vehicle-aware multi-access edge computing network[J].China Communications,2021,18(11):26-41.
[44]WANG R Y,WU H,CUI Y P,et al.Edge Offloading Strategy for the Multi-Base Station Game in Ultra-Dense Networks[J].Journal of Xidian University,2021,48(4):1-10.
[45]BOZORGCHENANI A,MASHHADI F,TARCHI D,et al.Multi-Objective Computation Sharing in Energy and Delay Constrained Mobile Edge Computing Environments[J].IEEE Transactions on Mobile Computing,2021,20(10):2992-3005.
[46]WANG P,LI K,XIAO B,et al.Multi-objective Optimization for Joint Task Offloading,Power Assignment,and Resource Allocation in Mobile Edge Computing[J].IEEE Internet of Things Journal,2022,9(14):11737-11748.
[47]YU X,SHI X Q,LIU Y X.Joint Optimization of OffloadingStrategy and Power in Mobile-Edge Computing[J].Computer Engineering,2020,46(6):20-25.
[48]GUO S,JIANG Q,DONG Y,et al.TaskAlloc:Online Tasks Allocation for Offloading in Energy Harvesting Mobile Edge Computing[C]//2019 IEEE International Conference on Parallel & Distributed Processing with Applications,Big Data & Cloud Computing,Sustainable Computing & Communications,Social Computing & Networking(ISPA/BDCloud/SocialCom/SustainCom).2019:116-123.
[49]ZHAO W,CHELLAPPA R,PHILLIPS P J,et al.Face recognition:A literature survey[J].ACM Computing Survey,2003,35(4):399-458.
[50]GUO S,XIAO B,YANG Y,et al.Energy-efficient dynamic offloading and resource scheduling in mobile cloud computing[C]//IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications.2016:1-9.
[51]SHANG Y,LI J,WU X.DAG-based Task Scheduling in Mobile Edge Computing[C]//2020 7th International Conference on Information Science and Control Engineering(ICISCE).2020:426-431.
[52]MING Z,LI X,SUN C,et al.Dependency-Aware Hybrid Task Offloading in Mobile Edge Computing Networks[C]//2021 IEEE 27th International Conference on Parallel and Distributed Systems(ICPADS).2021:225-232.
[53]LI B,NIU L,HUANG X et al.Mobility Prediction Based Computation Offloading Handoff Strategy for Vehicular Edge Computing[J].Journal of Electronics & Information Technology,2020,42(11):2664-2670.
[54]MESKAR E,LIANG B.Fair multi-resource allocation with external resource for mobile edge computing[C]//IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops(INFOCOM WKSHPS).2018:184-189.
[55]LIAO J X,WU X W.Resource Allocation and Task Scheduling Scheme in Priority-Based Hierarchical Edge Computing System[C]//2020 19th International Symposium on Distributed Computing and Applications for Business Engineering and Science(DCABES).2020:46-49.
[56]FAROOQ M O.Priority-Based Servicing of Offloaded Tasks in Mobile Edge Computing[C]//2021 IEEE 7th World Forum on Internet of Things(WF-IoT).2021:581-585.
[57]LUO Q,HU S,LI C,et al.Resource Scheduling in Edge Computing:A Survey[J].IEEE Communications Surveys & Tutorials,2021,23(4):2131-2165.

相关文章 15

[1]	于滨, 李学华, 潘春雨, 李娜. 基于深度强化学习的边云协同资源分配算法 Edge-Cloud Collaborative Resource Allocation Algorithm Based on Deep Reinforcement Learning 计算机科学, 2022, 49(7): 248-253. https://doi.org/10.11896/jsjkx.210400219
[2]	李梦菲, 毛莺池, 屠子健, 王瑄, 徐淑芳. 基于深度确定性策略梯度的服务器可靠性任务卸载策略 Server-reliability Task Offloading Strategy Based on Deep Deterministic Policy Gradient 计算机科学, 2022, 49(7): 271-279. https://doi.org/10.11896/jsjkx.210600040
[3]	方韬, 杨旸, 陈佳馨. D2D辅助移动边缘计算下的卸载策略优化 Optimization of Offloading Decisions in D2D-assisted MEC Networks 计算机科学, 2022, 49(6A): 601-605. https://doi.org/10.11896/jsjkx.210200114
[4]	刘漳辉, 郑鸿强, 张建山, 陈哲毅. 多无人机使能移动边缘计算系统中的计算卸载与部署优化 Computation Offloading and Deployment Optimization in Multi-UAV-Enabled Mobile Edge Computing Systems 计算机科学, 2022, 49(6A): 619-627. https://doi.org/10.11896/jsjkx.210600165
[5]	谢万城, 李斌, 代玥玥. 空中智能反射面辅助边缘计算中基于PPO的任务卸载方案 PPO Based Task Offloading Scheme in Aerial Reconfigurable Intelligent Surface-assisted Edge Computing 计算机科学, 2022, 49(6): 3-11. https://doi.org/10.11896/jsjkx.220100249
[6]	周天清, 岳亚莉. 超密集物联网络中多任务多步计算卸载算法研究 Multi-Task and Multi-Step Computation Offloading in Ultra-dense IoT Networks 计算机科学, 2022, 49(6): 12-18. https://doi.org/10.11896/jsjkx.211200147
[7]	邱旭, 卞浩卜, 吴铭骁, 朱晓荣. 基于5G毫米波通信的高速公路车联网任务卸载算法研究 Study on Task Offloading Algorithm for Internet of Vehicles on Highway Based on 5G MillimeterWave Communication 计算机科学, 2022, 49(6): 25-31. https://doi.org/10.11896/jsjkx.211100198
[8]	彭冬阳, 王睿, 胡谷雨, 祖家琛, 王田丰. 视频缓存策略中QoE和能量效率的公平联合优化 Fair Joint Optimization of QoE and Energy Efficiency in Caching Strategy for Videos 计算机科学, 2022, 49(4): 312-320. https://doi.org/10.11896/jsjkx.210800027
[9]	张海波, 张益峰, 刘开健. 基于NOMA-MEC的车联网任务卸载、迁移与缓存策略 Task Offloading,Migration and Caching Strategy in Internet of Vehicles Based on NOMA-MEC 计算机科学, 2022, 49(2): 304-311. https://doi.org/10.11896/jsjkx.210100157
[10]	王晨华, 侯守璐, 刘秀磊. 边云协同计算中成本感知的物联网数据处理方法 Cost-aware IoT Data Processing in Edge-Cloud Collaborative Computing 计算机科学, 2022, 49(11A): 211000101-7. https://doi.org/10.11896/jsjkx.211000101
[11]	梁俊斌, 张海涵, 蒋婵, 王天舒. 移动边缘计算中基于深度强化学习的任务卸载研究进展 Research Progress of Task Offloading Based on Deep Reinforcement Learning in Mobile Edge Computing 计算机科学, 2021, 48(7): 316-323. https://doi.org/10.11896/jsjkx.200800095
[12]	宋海宁, 焦健, 刘永. 高速公路中的移动边缘计算研究 Research on Mobile Edge Computing in Expressway 计算机科学, 2021, 48(6A): 383-386. https://doi.org/10.11896/jsjkx.200900212
[13]	范艳芳, 袁爽, 蔡英, 陈若愚. 车载边缘计算中基于深度强化学习的协同计算卸载方案 Deep Reinforcement Learning-based Collaborative Computation Offloading Scheme in VehicularEdge Computing 计算机科学, 2021, 48(5): 270-276. https://doi.org/10.11896/jsjkx.201000005
[14]	李振江, 张幸林. 减少核心网拥塞的边缘计算资源分配和卸载决策 Resource Allocation and Offloading Decision of Edge Computing for Reducing Core Network Congestion 计算机科学, 2021, 48(3): 281-288. https://doi.org/10.11896/jsjkx.200700025
[15]	姚泽玮, 林嘉雯, 胡俊钦, 陈星. 基于PSO-GA的多边缘负载均衡方法 PSO-GA Based Approach to Multi-edge Load Balancing 计算机科学, 2021, 48(11A): 456-463. https://doi.org/10.11896/jsjkx.210100191

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed