An Energy Consumption Minimization Optimization Scheme for HAP-Satellites Edge Computing

Low-earth orbit (LEO) satellites can provide computing services for ground users by carrying mobile edge computing servers. However, due to the high altitude of LEO satellites, ground users need to consume a lot of energy to communicate with them. So we leverage the high altitude platform (HAP) to cooperate with LEO satellites, called HAP-Satellites edge computing, and jointly provide computing services for ground users. An optimization problem is formulated to minimize the sum weighted energy consumption of all devices for HAP-Satellites edge computing. This is a mixed integer non-linear programming problem that is difficult to solve. So, we propose an intelligent heuristic algorithm to optimize task offloading and resource allocation. Simulation results demonstrate that the proposed scheme outperforms the other benchmark schemes in terms of weighted sum energy consumption.