Telecommunications Science ›› 2022, Vol. 38 ›› Issue (3): 113-132.doi: 10.11959/j.issn.1000-0801.2022022

Special Issue: 边缘计算

• Research and Development • Previous Articles     Next Articles

Review on resources allocation and pricing methods in mobile edge computing

Lushan ZOU1,2, Xiaowen HUANG1,3, Jingmin YANG1,4, Yifeng ZHENG1,2, Guanglin ZHANG3, Wenjie ZHANG1,2   

  1. 1 School of Computer Sciences, Minnan Normal University, Zhangzhou 363000, China
    2 Key Laboratory of Data Science and Intelligence Application, Fujian Province University, Minnan Normal University, Zhangzhou 363000, China
    3 School of Information Science and Technology, Donghua University, Shanghai 200051, China
    4 Department of Electronic Engineering, Taipei University of Technology, Taipei 106344, China
  • Revised:2022-01-26 Online:2022-03-20 Published:2022-03-01
  • Supported by:
    The National Natural Science Foundation of China(62141602);The Natural Science Foundation of Fujian Province of China(2021J011002);The Natural Science Foundation of Fujian Province of China(2021J011004);The Natural Science Foundation of Fujian Province of China(2020J01813)

Abstract:

Mobile edge computing (MEC) has ability of reducing network load and transmission delay, and improving user service experience by offloading computing tasks to edge servers.Therefore, MEC has attracted extensive attention and become a key technology of 5G.As one of the main issues of MEC, resource allocation has great significance in improving energy efficiency, shortening task delay and reducing cost.Firstly, the basic concept, reference architecture and technical advantages of MEC were introduced.Then, the up-to-date achievements of resources allocation and pricing strategies were summarized from both technical and economic aspects.Finally, some possible problems and challenges associated with resource allocation and pricing strategies in MEC were discussed, and the enabling methods to address these challenges were also proposed to provide reference for subsequent research and development.

Key words: mobile edge computing, resource allocation, pricing method, economic model, game theory

CLC Number: 

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