LEO Satellite and UAVs Assisted Mobile Edge Computing for Tactical Ad-Hoc Network: A Game Theory Approach

As an emerging technology, mobile edge computing (MEC) network paradigm provides great computing potential for edge services, which has been widely applied in friendly city environment. However, there are still many challenges to deploy MEC technology in harsh tactical communication environment due to poor communication conditions, limited computational resources, and hostile malicious interference. Thus, this article investigates the computational resource pricing and task offloading strategy in tactical MEC ad-hoc network, which consists of multiple tactical edge nodes, ground MEC servers, unmanned aerial vehicle-MEC (UAV-MEC) servers and a low-Earth orbit-MEC (LEO-MEC) satellite server. Each edge node can offload its partial computation-intensive task to the MEC servers to reduce computational delay and energy consumption. First, a multileader and multifollower Stackelberg game (MLMF-SG) which includes leader subgame for MEC servers and follower subgame for edge nodes, is proposed to formulate the interaction between servers and edge nodes. It has been proved that there exists a Stackelberg equilibrium (SE) in the proposed MLMF-SG. In order to decrease the delay, energy consumption, and resource overhead, the follower subgame is further formulated as a multimode computation task offloading game. With the help of the exact potential game (EPG), we prove that the follower subgame can converge to the Nash equilibrium (NE). To achieve the SE, a hierarchical distributed iterative algorithm is designed to maximize the utilities of the leaders and followers. Finally, the simulation results demonstrate that the proposed scheme can achieve better performance compared with the existing schemes.