Mobile-edge computing (MEC) is an innovative computing paradigm. Mobile devices can reduce local computation energy consumption and delay by offloading computation intensive tasks to the edge servers. In this paper, we first study the computation offloading problem for multiple mobile devices with independent task sets in the dense area of microcell base stations, where each microcell base station is equipped with a computationally limited MEC server. To reduce the task sets computation energy consumption and delay of the mobile devices as much as possible, adopting a game theoretic approach, the problem is formulated as a non-cooperative multi-mobile-device computation offloading strategy game. Through analysis, the Nash equilibrium existence and the finite improvement property of the game are proved. Then, we design a game theory based distributed computation offloading algorithm, namely GDCOA, and introduce a particle swarm optimization (PSO) based improving computation offloading policy algorithm named PSOIPA in it. GDCOA can reach an equilibrium state after a finite number of iterations. Finally, the simulation and comparison experiments corroborate that the proposed algorithm GDCOA in this paper can achieve better computation offloading performance.
LI Han, MENG Shunmei, CAI Zhicheng
. Game Theory and Particle Swarm Optimization Based Task Offloading Method in Mobile-Edge Computing[J]. Journal of Applied Sciences, 2023
, 41(3)
: 405
-418
.
DOI: 10.3969/j.issn.0255-8297.2023.03.004
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