Inter-Satellite Resource Balancing Based on Genetic Algorithm in Terrestrial-Satellite Networks

In recent years, the advancement of satellite networks has facilitated the provision of compute-intensive services to users, typically accomplished by allocating relevant resources through ground stations. However, suboptimal allocation strategies can result in load imbalance among satellites, leading to a decline in quality of service (QoS). Addressing the crucial challenge of inter-satellite resource balancing in terrestrial-satellite networks (TSNs) is imperative for enhancing QoS. This paper proposes a satellite resource balancing algorithm for TSNs, which optimizes the resources of the satellite constellation by considering the impact of different user tasks on the satellite load level. Furthermore, we investigate the offloading decisions of terrestrial users to minimize load imbalance among satellites while fulfilling latency requirements. To tackle the multi-dimensional optimization objectives and discrete decision variables, we introduce the non-dominated sorting genetic algorithm II (NSGA-II). Through extensive simulations, we demonstrate the effectiveness of the proposed algorithm in significantly improving satellite load balancing.