Simulation study demonstrates improved data transmission efficiency in UAV-assisted edge computing networks, indicating optimal trade-offs between flight position and ground clustering.
In this study, the air–ground integrated deployment method is studied for the unmanned aerial vehicle (UAV)‐enabled mobile edge computing (MEC) system. The UAV can help to reduce the delay and energy consumption of MEC. However, the limited coverage range of UAV limits the quality of data offloading. To improve the efficiency of data transmission, a hierarchical game model is designed. Ground nodes form multiple coalitions actively according to the position of UAV and the UAV adjusts the position based on the data distribution of ground networks. The relationship between the UAV and ground nodes is modelled as a Stackelberg game. A coalition formation game (CFG) is constructed for the data gathering among ground nodes. It is proved that the proposed CFG is an exact potential game with at least one Nash equilibrium. Moreover, the property of Stackelberg equilibrium is proven for the air–ground cooperative relationship. Based on the hierarchical model, a distributed air–ground integrated deployment algorithm is proposed to jointly optimise the position of the UAV and the coalition formation of ground nodes. The simulation results show that the proposed method promotes the efficiency of data transmission greatly and can converge to a stable state with reasonable iteration times.
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Yu et al. (2020) studied this question.
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