Distributed Task Offloading and Resource Purchasing in NOMA-enabled Mobile Edge Computing: Hierarchical Game Theoretical Approaches

As the computing resources and battery capacity of mobile devices are usually limited, it is a feasible solution to offload computation-intensive tasks generated by edge servers in (MEC). In this paper, we study multi-user multi-server task offloading problem systems, where all users compete for limited communication resources. We formulate with goal minimizing cost maximizing profits servers. propose hierarchical Economic Efficient Task Offloading Resource Purchasing (EETORP) framework that includes two-stage joint optimization process. Then, prove NP-complete. For first stage, as multi-channel access game (MCA-Game) theoretically existence at least one Nash equilibrium strategy MCA-Game. Next, game-based (GMCA) algorithm obtain analyze performance guarantee obtained worst case. second model resource allocation between Stackelberg theory, reformulate pricing purchasing (PAP-Game). property incentive compatibility equilibrium. A (GPAP) proposed. Finally, series both parameter experiments comparison carried out, which validate convergence effectiveness GMCA GPAP algorithms.