Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (11A): 240200010-7.doi: 10.11896/jsjkx.240200010

• Network & Communication • Previous Articles     Next Articles

Joint Optimization Method for Node Deployment and Resource Allocation Based on End-EdgeCollaboration

YANG Zheming1,3, ZUO Lulu 1,2,3, JI Wen 1,2   

  1. 1 Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China
    2 Pengcheng Laboratory,Shenzhen,Guangdong 518055,China
    3 School of Computer Science and Technology,University of Chinese Academy of Sciences,Beijing 100049,China
  • Online:2024-11-16 Published:2024-11-13
  • About author:YANG Zheming,born in 1996,doctoral student.His main research interests include multimedia systems,edge intelligence,network optimization,and visual IoT.
    JI Wen,born in 1976,Ph.D,professor,Ph.D supervisor.Her main research interests include vision processing units,end-edge-cloud computing systems,vision coding and transmission,intelligent multimedia computing,low-carbon computing,and optimization theory methods.
  • Supported by:
    National Key R & D Program of China(2023YFB4502805),National Natural Science Foundation of China(62072440) and Beijing Natural Science Foundation(L221004).

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Abstract: With the rapid development of IoT technology,edge computing shows its unique advantages in diverse application scenarios.The location deployment and resource allocation of edge servers become the key factors to improve the efficiency of task processing.However,this process faces significant challenges due to the wide distribution of end devices and the heterogeneous nature of edge servers.To effectively address these issues,this paper proposes a joint optimization method for node deployment and resource allocation based on end-edge collaboration,aiming to improve the overall performance of edge computing systems comprehensively.Our approach first utilizes a hierarchical clustering algorithm to effectively divide end devices into several regions based on their functional and geographic similarities.Subsequently,based on key metrics such as processing power,storage space,and network bandwidth of edge servers,the most suitable edge nodes in each region is decided.Finally,allocating tasks is guided by jointly optimizing node deployment and resource utilization.To validate the effectiveness of the proposed method,we conduct simulation experiments of different methods on public datasets.Experimental results show that our proposed method can improve the load balancing level by more than 30% and reduce task processing latency and energy consumption by more than 10%,compared to the existing methods.

Key words: Edge computing, Node deployment, Resource allocation, Load balancing, Task offloading

CLC Number: 

  • TP 311.5
[1]The Mobile Economy[EB/OL].[2023-07-16].https://www.gsma.com/mobileeconomy/.
[2]YANG Z M,HU D,GUO Q,et al.Visual E2C:AI-driven visual end-edge-cloud architecture for 6G in low-carbon smart cities [J].IEEE Wireless Communications,2023,30(3):204-210.
[3]ABBAS N,ZHANG Y,TAHERKORDI A,et al.Mobile edgecomputing:A survey [J].IEEE Internet of Things Journal,2017,5(1):450-465.
[4]MACH P,BECVAR Z.Mobile edge computing:A survey on ar-chitecture and computation offloading [J].IEEE Communications Surveys& Tutorials,2017,19(3):1628-1656.
[5]CRUZ P,ACHIR N,VIANA A C.On the edge of the deployment:A survey on multi-access edge computing [J].ACM Computing Surveys,2022,55(5):1-34.
[6]YANG Z M,JI W,GUO Q,et al.JAVP:Joint-aware video processing with edge-cloud collaboration for DNN inference[C]//Proceedings of the 31st ACM International Conference on Multimedia.ACM,2023:9152-9160.
[7]WANG S,ZHAO Y,XU J,et al.Edge server placement in mobile edge computing [J].Journal of Parallel and Distributed Computing,2019,127(5):160-168.
[8]LI B,HOU P,WU H,et al.Optimal edge server deployment and allocation strategy in 5G ultra-dense networking environments[J].Pervasive and Mobile Computing,2021,72:101312.
[9]LI B,HOU P,WU H,et al.Placement of edge server based on taskoverhead in mobile edge computing environment [J].Tran-sactions on Emerging Telecommunications Technologies,2021,32(9):e4196.
[10]LEE S,SHIN M K.Low cost mec server placement and associa-tion in 5g networks[C]//2019 International Conference on Informationand Communication Technology Convergence.IEEE,2019:879-882.
[11]YIN H,ZHANG X,LIU H H,et al.Edge provisioning withflexible server placement [J].IEEE Transactions on Parallel and Distributed Systems,2016,28(4):1031-1045.
[12]CUI G,HE Q,CHEN F,et al.Trading off between user covera-ge and network robustness for edge server placement [J].IEEE Transactions on Cloud Computing,2020,10(2):2178-2189.
[13]LU D,QU Y,WU F,et al.Robust server placement for edge computing[C]//2020 IEEE International Parallel and Distributed Processing Symposium.IEEE,2020:285-294.
[14]AHDERANTA T L,LTPPANEN T,RUHA L,et al.Edgecomputing server placement with capacitated location allocation [J].Journal of Parallel and Distributed Computing,2021,153(2):130-149.
[15]LI Y,ZHOU A,MA X,et al.Profit-aware edge server placement[J].IEEE Internet of Things Journal,2021,9(1):55-67.
[16]GUO Y,WANG S,ZHOU A,et al.User allocation-aware edge cloud placement in mobile edge computing[J].Software:Practice and Experience,2020,50(5):489-502.
[17]XU X,XUE Y,QI L,et al.Load-aware edge server placement for mobile edge computing in 5g networks[C]//International Conference on Service-Oriented Computing.Springer,2019:494-507.
[18]CHEN Y,LIN Y,ZHENG Z,et al.Preference-aware edge server placement in the internet of things [J].IEEE Internet of Things Journal,2021,9(2):1289-1299.
[19]QIN Z,XU F,XIE Y,et al.An improved top-k algorithm foredge servers deployment in smart city [J].Transactions on Emerging Telecommunications Technologies,2021,32(8):e4249.
[20]WANG F,HUANG X,NIAN H,et al.Cost-effective edge ser-ver placement in edge computing[C]//Proceedings of the 5th International Conference on Systems,Control and Communications.ACM,2019:6-10.
[21]CAO K,LI L,CUI Y,et al.Exploring placement ofheterogeneous edge servers for response time minimization in mobile edge-cloud computing [J].IEEE Transactions on Industrial Informatics,2020,17(1):494-503.
[22]MIRHOSEINI A,GOLDIE A,YAZGAN M,et al.A graphplacement methodology for fast chip design [J].Nature,2021,594(7862):207-212.
[23]WANG H,YANG R,YIN C,et al.Research on the difficulty of mobile node deployment's self-play in wireless ad hoc networks based on deep reinforcement learning [J].Wireless Communications and Mobile Computing,2021,2021(1):1-13.
[24]YANG Z M,JI W,WANG Z.Adaptive joint configuration optimization for collaborative inference in edge-cloud systems[J].Science China Information Sciences,2024,67(4):1-2.
[25]YANG Z M,LIANG B,JI W.An intelligent end-edge-cloud architecture for visual iot assisted healthcare systems [J].IEEE Internet of Things Journal,2021,8(23):16779-16786.
[26]LAI P,HE Q,ABDELEAZEK M,et al.Optimal edge user allocation in edge computing with variable sized vector bin packing[C]//International Conference on Service-Oriented Computing.Springer,2018:230-245.
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