Routing Optimization of LEO Satellite Network Based on Genetic Ant Colony Algorithm

Traditional satellite networks should not guarantee Quality of Service (QoS) due to unbalanced resource utilization and high load. Therefore, a routing algorithm based on load balancing is proposed, and a genetic ant colony algorithm is used to guarantee multi-constrained QoS. Firstly, the potential traffic demand of the whole network is predicted and the heuristic function is optimized. Then, the path cost and pheromone update strategy are improved. Finally, the optimal path satisfying load balancing and QoS constraints is selected. Through simulation experiments, it is found that the proposed algorithm can effectively balance the service load of the satellite network, and significantly improve the performance in the aspects of end-to-end delay and packet loss rate.