Congestion-Aware Scheduling for Software-Defined SAG Networks

As a successful solution for global communications, Space-Air-Ground (SAG) networks, have drawn extensive attention. Satellites are influenced by geographical features as a way of space communications. Since the traffic congestion may occur in densely populated cities, leading to serious latency and throughput collapses. To solve this problem, we first introduce Software Defined Networks (SDN) into satellites and then propose a load balancing approach to improve communication performances. However, the SDN Space-Air-Ground networks need a cooperative communication process, we consider this problem as an SDN-enabled routers placement problem, so that we can decide the exactly traditional routers are upgrading to ensure the robustness of hybrid networks. Based on the hybrid Space-Air-Ground networks, we design a load balancing strategy to distribute traffic among networks optimally, so that the total congested links are minimized in our proposed model. For better performance in Space-Air-Ground networks, we propose a resilient congestion estimate scheme. Detouring traffic around the nearby satellites to optimize traffic load is a decision based on the network condition. Simulation results illustrate that our proposed method outperforms traditional satellite network methods by improving 6.5% and 4.4% packet loss rate, and 11.6% and 8.3% higher throughput respectively.