Computer Science ›› 2021, Vol. 48 ›› Issue (1): 49-57.doi: 10.11896/jsjkx.200600129

Special Issue: Intelligent Edge Computing

• Intelligent Edge Computing • Previous Articles     Next Articles

Multi-user Task Offloading Based on Delayed Acceptance

MAO Ying-chi, ZHOU Tong, LIU Peng-fei   

  1. College of Computer and Information,Hohai University,Nanjing 211100,China
  • Received:2020-06-20 Revised:2020-11-19 Online:2021-01-15 Published:2021-01-15
  • About author:MAO Ying-chi,born in 1976,Ph.D,professor,is a senior member of China Computer Federation.Her main research interests include distributed computing and parallel processing,IoT,and edge intelligence computing.
    ZHOU Tong,born in 1997,M.S.candidate.His main research interests include distributed computing,IoT and edge intelligence computing.
  • Supported by:
    China National Key R&D Program(2018YFC0407105),National Natural Science Foundation of China(61832005) and Technology Project of China Huaneng Group Headquarters(HNKJ19-H12).

Abstract: With the application of artificial intelligence,the demand for computing resources is higher and higher.Due to the limi-ted computing power and energy storage,mobile devices can not deal with this kind of computing intensive applications with real-time requirements.Mobile edge computing (MEC) can provide computing offload service at the edge of wireless network,so as to reduce the delay and save energy.Aiming at the problem of multi-user dependent task offloading,a user dependent task model is established based on the comprehensive consideration of delay and energy consumption.The multi-user task offloading strategy based on delay acceptance (MUTODA) is proposed to solve the problem of minimizing energy consumption under delay constraints.MUTODA solves the problem of multi-user task offloading through two steps of non dominated single user optimal offloading strategy and adjustment strategy to solve resource competition.The experimental results show that compared with the benchmark strategy and heuristic strategy,the multi-user task offloading strategy based on delayed acceptance can improve about 8% user satisfaction and save 30%~50% of the energy consumption of mobile terminals.

Key words: Game theory, Mobile edge computing, Task interdependence, Task offloading

CLC Number: 

  • TP399
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