Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (1): 58-64.doi: 10.11896/jsjkx.200900079

Special Issue: Intelligent Edge Computing

• Intelligent Edge Computing • Previous Articles     Next Articles

User Allocation Approach in Dynamic Mobile Edge Computing

TANG Wen-jun, LIU Yue, CHEN Rong   

  1. Department of Information Science and Technology,Dalian Maritime University,Dalian,Liaoning 116026,China
  • Received:2020-09-09 Revised:2020-12-07 Online:2021-01-15 Published:2021-01-15
  • About author:TANG Wen-jun,born in 1994,Ph.D student.Her main research interests include crowdsourcing workflows,crowd sourcing task assignment and web service testing.
    CHEN Rong,born in 1969,Ph.D,professor,is a member of the IEEE and a member of the ACM.His main research interests include software diagnosis,collective intelligence,activity recognition,Internet and mobile computing.
  • Supported by:
    National Natural Science Foundation of China(61672122,61902050,61602077),Fundamental Research Funds for the Central Universities of Ministry of Education of China(3132019355),ERNET Innovation Project (NGII20190627) and China Postdoctoral Science Foundation (2020M670736).

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Abstract: In edge computing environment,matching suitable servers for users is a key issue,which can effectively improve the quality of service.In this paper,the edge user assignment (EUA) problem is converted into a bipartite graph matching problem constrained by distance and server resources,and it is modeled as a 0-1 integer programming problem for optimal assignment solution.In the offline state,the optimization model based on exact algorithm can obtain the optimal assignment strategy,but its solution time is too long,and it cannot process large-scale of data,which is not suitable for the real service environment.Therefore,the online user assignment method based on heuristic strategy is proposed to optimize the user-server assignment under limited time.The experimental results show that the competitive ratio obtained by Proximal Heuristic online method (PH) can reach close to 100%,and can obtain a better assignment solution within an acceptable time.At the same time,the online PH method performs better than other basic heuristic methods.

Key words: Bipartite graph matching, Computing offloading, Edge computing, Edge user allocation, Heuristic method

CLC Number: 

  • TP311.5
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