Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (1): 1-10.doi: 10.11896/jsjkx.200900150

Special Issue: Intelligent Edge Computing

• Intelligent Edge Computing • Previous Articles     Next Articles

Edge Computing Enabling Industrial Internet:Architecture,Applications and Challenges

LI Hui1,2, LI Xiu-hua1,2, XIONG Qing-yu1,2, WEN Jun-hao1,2, CHENG Lu-xi1,2,3, XING Bin3   

  1. 1 Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education,Chongqing 401331,China
    2 School of Big Data & Software Engineering,Chongqing University,Chongqing 401331,China
    3 Chongqing Innovation Center of Industrial Big-Data Co.Ltd,Chongqing 400000,China
  • Received:2020-09-21 Revised:2020-12-02 Online:2021-01-15 Published:2021-01-15
  • About author:LI Hui,born in 1997,postgraduate.His main research interests include Internet of things,edge computing,cloud computing and deep learning.
    CHENG Lu-xi,born in 1988,Ph.D.His main research interests include Internet of vehicles,big data,edge computing and cloud computing.
  • Supported by:
    National Natural Science Foundation of China(61902044,61672117,62072060),National Key R & D Program of China(2018YFB2100100,2018YFF0214700),Chongqing Research Program of Basic Research and Frontier Technology(cstc2019jcyj-msxmX0589),Key Research Program of Chongqing Science & Technology Commission (CSTC2017jcyjBX0025,CSTC2019jscx-zdztzxX0031) and Fundamental Research Funds for the Central Universities(2020CDJQY-A022).

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Abstract: Industrial Internet integrates advanced technologies such as 5G communication and artificial intelligence,and integrates various sensors and controllers with perception and control capabilities into the industrial production process to optimize production processes,reduce costs and increase productivity.Due to the centralized deployment of the traditional cloud computing mo-del,the location of computing node is usually far away from the smart terminal,which is difficult to meet the requirements of the industrial field for high real-time and low latency.By sinking computing,storage and network resources to the edge of the industrial network,edge computing can respond to device requests more conveniently,meet key requirements such as intelligent access,real-time communication and privacy protection in the Industrial Internet environment,and realize intelligent green communication.This paper firstly introduces the development status of the Industrial Internet and the related concepts of edge computing,then systematically discusses the Industrial Internet edge computing architecture and the core technologies that promote the development of Industrial Internet edge computing.Finally,it lists some successful application cases of edge computing and elaborates the current status and challenges of applying edge computing technology in Industrial Internet.

Key words: Applications and challenges, Architecture, Edge computing, Edge-cloud collaboration, Industrial Internet

CLC Number: 

  • TP393
[1] Ministry of Industry and Information Technology.Industrial Internet Industry Application Promotion Association [EB/OL].http://www.miit.gov.cn/n973401/n5993937/n5993953/c7883868/content.html.
[2] Ministry of Industry and Information.The IndustrialLInternet Logo Analysis Laboratory became the first batch of industry alliance laboratories [EB/OL].http://www.miit.gov.cn/n973401/n5993937/n5993953/c8017365/content.html.
[3] Industrial Internet Industry Alliance.Industrial Internet Plat-form White Paper (2017) [EB/OL].http://www.aii-alliance.org/bps/20200302/858.html.
[4] REN J,YU G,HE Y,et al.Collaborative cloud and edge computing for latency minimization[J].IEEE Transactions on Vehicular Technology,2019,68(5):5031-5044.
[5] ZHANG J,CHEN B,ZHAO Y,et al.Data security and privacy-preserving in edge computing paradigm:Survey and open issues[J].IEEE Access,2018,6:18209-18237.
[6] ZHAO M.Overview of Edge Computing Technology and Application[J].Computer Science,47(6A):268-272.
[7] SATYANARAYANAN M,BAHL P,CACERES R,et al.The case for vm-based cloudlets in mobile computing[J].IEEE pervasive Computing,2009,8(4):14-23.
[8] BONOMI F,MILITO R,ZHU J,et al.Fog computing and its role in the internet of things[C]//Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing.2012:13-16.
[9] 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.
[10] SHI W,CAO J,ZHANG Q,et al.Edge computing:Vision and challenges[J].IEEE Internet of Things Journal,2016,3(5):637-646.
[11] OpenEdge.OpenEdge architecture [EB/OL].https://openedge.-tech/zh/.
[12] Edge Computing Industry Alliance (ECC) and Industrial Internet Industry Alliance (AII).Edge Computing IT Infrastructure White Paper 1.0 [EB/OL].http://www.ecconsortium.org/Lists/show/id/375.html.
[13] China Mobile 5G Joint Innovation Center.Blockchain+EdgeComputing Technology White Paper [EB/OL].http://pg.jrj.com.cn/acc/Res/CN_RES/INDUS/2020/7/2/57f00099-d938 -48e0-8f57-3276236af94b.pdf.
[14] SHAFI M,MOLISCH A F,SMITH P J,et al.5G:A tutorialoverview of standards,trials,challenges,deployment,and practice[J].IEEE Journal on Selected Areas in Communications,2017,35(6):1201-1221.
[15] Cisco.Cisco annual internet report (2018－2023) white paper[EB/OL].https://www.cisco.com/c/en/us/solutions/colla-teral/executive-perspectives/annual-internet-report/white-paper-c11-741490.html.
[16] QIU T,CHI J,ZHOU X,et al.Edge Computing in Industrial Internet of Things:Architecture,Advances and Challenges[J].IEEE Communications Surveys Tutorials,2020,22(4):2462-2488.
[17] CHEN X,JIAO L,LI W,et al.Efficient multi-user computation offloading for mobile-edge cloud computing[J].IEEE/ACM Transactions on Networking,2015,24(5):2795-2808.
[18] XIA Y N,MA Y Y,XIAO X,et al.Research review on the current situation of mobile edge computing technology and several key issues[J].Journal of Guangzhou University (Natural Science Edition).2019,18(2):17-29.
[19] NING Z,DONG P,WANG X,et al.Deep reinforcement learning for intelligent Internet of vehicles:An energy-efficient computational offloading scheme[J].IEEE Transactions on Cognitive Communications,2019,5(4):1060-1072.
[20] XU X,ZHANG X,GAO H,et al.BeCome:Blockchain-enabled computation offloading for IoT in mobile edge computing[J].IEEE Transactions on Industrial Informatics,2019,16(6):4187-4195.
[21] SUN C,HUI L,LI X,et al.Task Offloading for End-Edge-Cloud Orchestrated Computing in Mobile Networks[C]//2020 IEEE Wireless Communications and Networking Conference (WCNC).2020:1-6.
[22] KREUTZ D,RAMOS F M,VERISSIMO P E,et al.Software-defined networking:A comprehensive survey[J].Proceedings of the IEEE,2014,103(1):14-76.
[23] XIA W,WEN Y,FOH C H,et al.A survey on software-defined networking[J].IEEE Communications Surveys Tutorials,2014,17(1):27-51.
[24] BAKTIR A C,OZGOVDE A,ERSOY C J I C S,et al.How can edge computing benefit from software-defined networking:A survey,use cases,and future directions[J].IEEE Communications Surveys Tutorials,2017,19(4):2359-2391.
[25] CHENG X,WU Y,MIN G,et al.Network function virtualization in dynamic networks:A stochastic perspective[J].IEEE Journal on Selected Areas in Communications,2018,36(10):2218-2232.
[26] MIJUMBI R,SERRAT J,GORRICHO J L,et al.Network function virtualization:State-of-the-art and research challenges[J].IEEE Communications surveys tutorials,2015,18(1):236-262.
[27] YI B,WANG X,LI K,et al.A comprehensive survey of network function virtualization[J].Computer Networks,2018,133:212-262.
[28] COSTA-REQUENA J,SANTOS J L,GUASCHV F,et al.SDN and NFV integration in generalized mobile network architecture[C]//2015 European Conference on Networks and Communications (EuCNC).2015:154-158.
[29] LYU Z,XIU W J I I O T J.Interaction of edge-cloud computing based on SDN and NFV for next generation IoT[J].IEEE Internet of Things Journal,2019.
[30] QIAO X,REN P,DUSTDAR S,et al.A new era for web AR with mobile edge computing[J].IEEE Internet Computing,2018,22(4):46-55.
[31] ZAHOOR S,JAVAID S,JAVAID N,et al.Cloud-fog-basedsmart grid model for efficient resource management[J].Sustainability,2018,10(6):2079.
[32] KALOXYLOS A J I C S M.A survey and an analysis of network slicing in 5G networks[J].IEEE Communications Stan-dards Magazine,2018,2(1):60-65.
[33] ORDONEZ-LUCENA J,AMEIGEIRAS P,LOPEZ D,et al.Networkslicing for 5G with SDN/NFV:Concepts,architectures,and challenges[J].IEEE Communications Magazine,2017,55(5):80-87.
[34] WANG X F.Smart Edge Computing:A Bridge from the Internet of Everything to the Empowerment of Everything[J].People's Forum· Frontiers of Academic Research,2020(9):4-17.
[35] WANG X,HAN Y,LEUNG V C,et al.Convergence of edge computing and deep learning:A comprehensive survey[J].IEEE Communications Surveys Tutorials,2020,22(2):869-904.
[36] KRIZHEVSKY A,SUTSKEVER I,HINTON G E.Imagenetclassification with deep convolutional neural networks[C]//Advances in Neural Information Processing Systems.2012:1097-1105.
[37] YANG J,ZHANG J,MA C,et al.Deep learning-based edge ca-ching for multi-cluster heterogeneous networks[J].Neural Computing Applications,2019:1-12.
[38] YANG Y,CHEN X,CHEN Y,et al.Green-Oriented Offloading and Resource Allocation by Reinforcement Learning in MEC[C]//2019 IEEE International Conference on Smart Internet of Things (SmartIoT).2019:378-382.
[39] ZHANG H,CHEN S,ZOU P,et al.Research and Application of Industrial Equipment Management Service System Based on Cloud-Edge Collaboration[C]//2019 Chinese Automation Congress (CAC).2019:5451-5456.
[40] LI X,WAN J,DAI H-N,et al.A hybrid computing solution and resource scheduling strategy for edge computing in smart manufacturing[J].IEEE Transactions on Industrial Informatics,2019,15(7):4225-4234.
[41] SANKARANARAYANAN S,RODRIGUES J J,SUGUMA-RAN V,et al.Data Flow and Distributed Deep Neural Network based low latency IoT-Edge computation model for big data environment[J].Engineering Applications of Artificial Intelligence,2020,94:103785.
[42] CONTRERAS-CASTILLO J,ZEADALLY S,GUERRERO-IBAÑEZ J A J I I O T J.Internet of vehicles:architecture,protocols,and security[J].IEEE internet of things Journal,2017,5(5):3701-3709.
[43] SOUZA A M D,OLIVEIRA H F,ZHAO Z,et al.Enhancing Sensing and Decision-Making of Automated Driving Systems With Multi-Access Edge Computing and Machine Learning[J].IEEE Intelligent Transportation Systems Magazine,2020,PP(99).
[44] LIU S,LIU L,TANG J,et al.Edge computing for autonomous driving:Opportunities and challenges[J].Proceedings of the IEEE,2019,107(8):1697-1716.
[45] YANG S R,SU Y J,CHANG Y Y,et al.Short-Term TrafficPrediction for Edge Computing-Enhanced Autonomous and Connected Cars[J].IEEE Transactions on Vehicular Technology,2019,68(4):3140-3153.
[46] WANG Z,GAO Y,FANG C,et al.Optimal control design for connected cruise control with edge computing,caching,and control[C]//IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).2019:1-6.
[47] Cisco.2020 Global Networking Trends Report[EB/OL].https://www.cisco.com/c/m/en_us/solutions/enterprise-networks/networking-report.html#.
[48] CARDARELLI E,DIGANI V,SABATTINI L,et al.Cooperative cloud robotics architecture for the coordination of multi-AGV systems in industrial warehouses[J].Mechatronics,2017,45:1-13.
[49] CHEN Y D.Industrial Application Based on Edge Computing:Automatic Guided Car Control System[J].Computer Integrated Manufacturing System,2019,25(12):3191-3198.
[50] DING K,CHEN D S,WANG Y,et al.Smart Factory Industrial Internet of Things Architecture and Autonomous Production Control Technology Based on Cloud-Edge Collaboration[J].Computer Integrated Manufacturing System,2019,25(12):3127-3138.
[51] People's Daily Online.2019 National Fire Report [EB/OL].http://society.people.com.cn/n1/2020/0111/c1008-31544259.html.
[52] LONG C,CAO Y,JIANG T,et al.Edge computing framework for cooperative video processing in multimedia IoT systems[J].IEEE Transactions on Multimedia,2017,20(5):1126-1139.
[53] WU X,DUNNE R,ZHANG Q,et al.Edge computing enabled smart firefighting:opportunities and challenges[C]//Proceedings of the Fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies.2017:1-6.
[54] ZHANG Q,ZHANG Q,SHI W,et al.Distributed collaborative execution on the edges and its application to amber alerts[J].IEEE Internet of Things Journal,2018,5(5):3580-3593.
[55] XIAO Y,JIA Y,LIU C,et al.Proceedings of the IEEE[J].2019,107(8):1608-1631.
[56] ROMAN R,LOPEZ J,MAMBO M J F G C S.Mobile edge computing,fog et al.:A survey and analysis of security threats and challenges[J].Future Generation Computer Systems,2018,78:680-698.
[57] MUKHERJEE M,MATAM R,SHU L,et al.Security and privacy in fog computing:Challenges[J].IEEE Access,2017,5:19293-19304.
[58] LYU L,NANDAKUMAR K,RUBINSTEIN B,et al.PPFA:Privacy preserving fog-enabled aggregation in smart grid[J].IEEE Transactions on Industrial Informatics,2018,14(8):3733-3744.
[59] SHI W,DUSTDAR S J C.The promise of edge computing[J].Computer,2016,49(5):78-81.
[60] HONG C H,VARGHESE B J A C S.Resource management in fog/edge computing:a survey on architectures,infrastructure,and algorithms[J].ACM Computing Surveys,2019,52(5):1-37.
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