Journal of Xidian University ›› 2021, Vol. 48 ›› Issue (4): 1-10.doi: 10.19665/j.issn1001-2400.2021.04.001

• Information and Communications Engineering & Electronic Science and Technology •     Next Articles

Edge offloading strategy for the multi-base station game in ultra-dense networks

WANG Ruyan1,2,3(),WU He1,2,3(),CUI Yaping1,2,3(),WU Dapeng1,2,3(),ZHANG Hong1,2,3()   

  1. 1. School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
    2. Key Laboratory of Optical Communication and Networks in Chongqing,Chongqing 400065,China
    3. Key Laboratory of Ubiquitous Sensing and Networking in Chongqing,Chongqing 400065,China
  • Received:2020-01-06 Online:2021-08-30 Published:2021-08-31
  • Contact: Yaping CUI E-mail:wangry@cqupt.edu.cn;943091165@qq.com;cuiyp@cqupt.edu.cn;wudp@cqupt.edu.cn;hongzhang@cqupt.edu.cn

Abstract:

Mobile edge computing provides powerful computing capabilities for the wireless network to enrich the user experience.However,in the current mobile edge computing network,the problems of small coverage density and hotspot overload of the central node should be skillfully overcome.The combination of the ultra-dense network and mobile edge computing can provide a feasible solution for addressing the above problems.A distributed edge computing architecture for ultra-dense networks is designed,and a multi-base station game offloading algorithm is proposed to minimize the system overhead.In the proposed algorithm,the lagrange multiplier method is used to solve the problem of computing resource allocation,and then the matching game theory is exploited to obtain the optimal offloading strategy,so that the mutual benefits of both users and mobile edge computing servers are maximized.Simulation results show that compared with the random and greedy offloading algorithms,the proposed algorithm achieves a significant reduction in the system overhead,with the average overhead saving being up to 28.66%.

Key words: mobile edge computing, matching game, offloading, resource allocation

CLC Number: 

  • TN929.5

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