Joint Task Offloading and Resource Allocation Strategy for Hybrid MEC-Enabled LEO Satellite Networks: A Hierarchical Game Approach

The multi-access edge computing (MEC)-enabled low Earth orbit (LEO) satellite network is a promising approach to meet the growing ubiquitous diverse computation demands around the world. In this paper, a joint task offloading and resource allocation strategy is proposed for hybrid MEC-enabled LEO satellite networks, where two types of MEC tasks, namely delay-sensitive edgy-cloud task and data-and computation-intensive cloudy-edge task, are considered simultaneously. Specifically, we first design the cost functions for the two types of tasks, which take the delay-sensitive feature of edgy-cloud task and data-and computation-intensive characteristics of cloudy-edge task into consideration. Then, an overall terminal cost minimization problem is formulated for task offloading and resource allocation under the communication and computation capability constraints and the service delay requirements. In practice, terminals usually only care about their own costs, but satellites pursue the overall cost minimization of all the served terminals. Thus, considering the individual and collective rationality simultaneously, a two-level hierarchical game is constructed to solve the formulated problem. In the upper level, a hedonic coalition formation game is established, which enables each terminal to make the coalition selection and task offloading decision based on the designed coalition switch rule. In the lower level, the joint channel and power allocation in each coalition is first formulated as a noncooperative game to represent the individual rationality of each terminal. Then, each satellite performs the optimal computation resource allocation to maximize the coalition value with collective rationality. We prove that the Nash equilibrium (NE) for the noncooperative game exists and the coalition partition converges to a Nash stable state. Simulation results are provided to demonstrate the superiority of the proposed strategy.