Chinese Journal on Internet of Things ›› 2023, Vol. 7 ›› Issue (1): 140-148.doi: 10.11959/j.issn.2096-3750.2023.00313

• Theory and Technology • Previous Articles     Next Articles

Partial computation offloading method based on joint resource allocation for mobile edge computing

Yao LIU1,2, Yueyuan HE3, Hongjing ZHOU3, Chaoliang LI3, Chuang LI2,3   

  1. 1 School of Digital Media and Humanities, Hunan University of Technology and Business, Changsha 410205, China
    2 Changsha Social Laboratory of Artificial Intelligence, Changsha 410205, China
    3 School of Computer Science, Hunan University of Technology and Business, Changsha 410205, China
  • Revised:2022-11-21 Online:2023-03-30 Published:2023-03-01
  • Supported by:
    The National Natural Science Foundation of China(62002115);The Scientific Research Project of the Department of Education of Hunan Province(20C0538);The Scientific Research Project of the Department of Education of Hunan Province(21A0376);The Natural Science Foundation of Hunan Province(2020JJ4250);The Project of Hunan Social Science Achievement Appraisal Committee(XSP21YBZ113);The Project of Innovation Driven Program for Young Teachers(2020QD08)

Abstract:

In order to meet the requirements of users for computing-intensive tasks and solve the problems of limited computing resources and energy of mobile terminals, a partial offloading method was proposed for multi-user mobile edge computing system with orthogonal frequency division multiple access by setting constraints such as task delay, device energy and communication resources, aiming at optimizing task delay.The initial offloading ratio was set and the communication resource was allocated under the condition of satisfying the user’s minimum delay.And then the remaining computing resource was allocated according to the server’s computing capability.Finally, the offload ratio was optimized according to the resource allocation.Simulation results show that this method can reduce the delay of task computing and the energy consumption of mobile terminals.

Key words: mobile edge computing, computation offloading, resource allocation

CLC Number: 

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