Journal of Xidian University ›› 2020, Vol. 47 ›› Issue (2): 126-134.doi: 10.19665/j.issn1001-2400.2020.02.017

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Collaborative offloading of overloaded MEC servers in ultra-dense heterogeneous networks

WANG Ren1,2,WANG Yi1,2(),HU Yanjun1,JIANG Fang1,XU Yaohua1   

  1. 1.Ministry of Education Key Laboratory of Intelligent Computing & Signal Processing,Anhui University, Hefei 230601, China
    2.Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
  • Received:2019-07-30 Online:2020-04-20 Published:2020-04-26
  • Contact: Yi WANG


Mobile Edge Computing (MEC) can perform computational task offloading with the help of edge servers, and is no longer limited by the power of mobile terminals (MTs). When the edge server is overloaded, it often chooses to queue, postpone or reject the MT’s offloading request. QoS (Quality of Service) of users will deteriorate greatly due to service disruption and extended waiting, but the existing research work does not consider how the MEC-BS can relieve load pressure at this time. In this paper, we study how to enhance the computing offloading service of the MEC-BS by offloading the task of the overloaded base station to the other MEC-BS in the same collaboration space. Combining the penalty function with the two-step quasi-newton method, an optimization algorithm is proposed to minimize the joint utility function including the total delay and energy consumption of the edge computing network. Empirical factors are used to adjust the optimization deviation according to the different needs of the optimization target for time delay or energy efficiency. Simulation results show that the proposed scheme is better than two other schemes in improving the system performance and convergence speed.

Key words: mobile edge computing, overload, heterogeneous networks, collaborative offloading, joint optimization

CLC Number: 

  • TN929.5