Computer Science

Computer Science ›› 2026, Vol. 53 ›› Issue (2): 396-405.doi: 10.11896/jsjkx.250300088

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Game Theory-based Optimization of Flight Paths and Task Offloading in UAV-assisted MECSystems

WEI Manyi, WANG Gaocai, WEN Yihu   

  1. School of Computer and Electronic Information,Guangxi University,Nanning 530004,China
  • Received:2025-03-17 Revised:2025-06-06 Published:2026-02-10
  • About author:WEI Manyi,born in 2000,postgra-duate.Her main research interests include computer network and mobile edge computing.
    WANG Gaocai,born in 1976,Ph.D,professor,doctoral supervisor.His main research interests include computer network,performance evaluation and network security.
  • Supported by:
    National Natural Science Foundation of China(62062007) and Natural Science Foundation of Guangxi,China(2025GXNSFAA069236).

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Abstract: In traditional MEC systems,fixed MEC server deployments are susceptible to communication blockages due to multipath and non-line-of-sight(NLOS) effects.UAV-assisted MEC has emerged as a solution.This paper proposes a UAV-assisted MEC system with a clustering-based flight path optimization method to extend the UAV’s operational time and the network lifetime.K-means clustering partitions users into clusters,and the shortest UAV flight path problem among cluster centers is formulated as a TSP and solved using Chaos Game Optimization(CGO) combined with 2-Opt.A potential game-based task offloading strategy is then designed to optimize system energy consumption and latency from the users’ perspective.The global optimization problem is modeled as a potential game with at least one Nash Equilibrium(NE),which corresponds to the global optimal solution.Experimental results show that the proposed methods effectively minimize system energy consumption and latency while ensuring complete service coverage.

Key words: Potential game, Chaos game, Mobile edge computing, Unmanned Aerial Vehicle, Task offloading

CLC Number: 

  • TP301
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