Potential Game Based Task Offloading in Aerial-Aided Edge Computing

The proliferation of Internet of Things applications has driven rapid Mobile Edge Computing (MEC) systems development by various Edge Service Providers (ESPs), creating a competitive computing market. Handling all received tasks from each ESP individually can significantly degrade the service performance of the MEC system. To enhance flexibility in network workload and service coverage, unmanned aerial vehicles (UAVs) have been employed in the MEC system. This paper proposes a potential game based trustful task offloading scheme for the multiple EPSs scenario in UAV-assisted MEC. Specifically, we formulate the Multiple ESPs Task Offloading (METO) problem into a potential game and prove the existence of Nash Equilibrium (NE). To guarantee the security of resource trading among different EPSs, we propose a blockchain-based sharing mechanism that converges to NE. Additionally, a reputation smart contract assesses ESPs' Quality of Service (QoS), influencing task allocation. Extensive simulations show our approach outperforms traditional baselines in maximizing each ESP's utility.