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A Multi-Leader Multi-Follower Stackelberg Game for Coalition-Based UAV MEC Networks

Jiaxin Chen, Qihui Wu, Yuhua Xu, Nan Qi, Tao Fang, Luliang Jia, Chao Dong

2021IEEE Wireless Communications Letters52 citationsDOI

Abstract

In this letter, we investigate the joint optimization of computation offloading, channel allocation and position deployment problem for coalition-based unmanned aerial vehicle (UAV) mobile edge computing networks. To characterize the hierarchical offloading feature in coalition-based UAV network, we propose the hierarchical framework and formulate a discrete multi-leader multi-follower energy minimization Stackelberg game. In addition, we prove that the multi-leader subgame and multi-follower subgame are exact potential games with Nash equilibrium. Then the existence of Stackelberg equilibrium (SE) is guaranteed. The spatial adaptive play-best response based hierarchical iterative learning (SAP-BRHIL) algorithm is proposed to achieve the SE. The simulation results show that the proposed SAP-BRHIL algorithm can achieve the lowest network energy consumption compared with some existing approaches.

Topics & Concepts

Stackelberg competitionComputer scienceSubgameNash equilibriumMathematical optimizationMobile edge computingComputation offloadingSubgame perfect equilibriumPotential gameGame theoryEnergy consumptionDistributed computingEnhanced Data Rates for GSM EvolutionBest responseEdge computingArtificial intelligenceMathematicsMathematical economicsBiologyEcologyEpsilon-equilibriumUAV Applications and OptimizationIoT and Edge/Fog ComputingDistributed Control Multi-Agent Systems
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