• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

An Offloading Strategy for Multi-User Energy Consumption Optimization in Multi-MEC Scene

Vol. 14, No. 10, October 31, 2020
10.3837/tiis.2020.10.006, Download Paper (Free):

Abstract

Mobile edge computing (MEC) is capable of providing services to smart devices nearby through radio access networks and thus improving service experience of users. In this paper, an offloading strategy for the joint optimization of computing and communication resources in multi-user and multi-MEC overlapping scene was proposed. In addition, under the condition that wireless transmission resources and MEC computing resources were limited and task completion delay was within the maximum tolerance time, the optimization problem of minimizing energy consumption of all users was created, which was then further divided into two subproblems, i.e. offloading strategy and resource allocation. These two subproblems were then solved by the game theory and Lagrangian function to obtain the optimal task offloading strategy and resource allocation plan, and the Nash equilibrium of user offloading strategy games and convex optimization of resource allocation were proved. The simulation results showed that the proposed algorithm could effectively reduce the energy consumption of users.


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Cite this article

[IEEE Style]
Z. Li and Q. Zhu, "An Offloading Strategy for Multi-User Energy Consumption Optimization in Multi-MEC Scene," KSII Transactions on Internet and Information Systems, vol. 14, no. 10, pp. 4025-4041, 2020. DOI: 10.3837/tiis.2020.10.006.

[ACM Style]
Zhi Li and Qi Zhu. 2020. An Offloading Strategy for Multi-User Energy Consumption Optimization in Multi-MEC Scene. KSII Transactions on Internet and Information Systems, 14, 10, (2020), 4025-4041. DOI: 10.3837/tiis.2020.10.006.

[BibTeX Style]
@article{tiis:23918, title="An Offloading Strategy for Multi-User Energy Consumption Optimization in Multi-MEC Scene", author="Zhi Li and Qi Zhu and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2020.10.006}, volume={14}, number={10}, year="2020", month={October}, pages={4025-4041}}