Distributed Anti-Cascading Routing Scheme Based on Fuzzy Logic in LEO Satellite Networks

LEO satellite networks provide global users with satellite internet services, yet the risk of cascading failures severely threatens the reliable operation of the network. Failures rapidly propagate from congested and overloaded satellites to normal satellites, causing the network to be trapped in a vicious cycle of periodic failures, unable to return to a stable state capable of providing regular services. Existing routing schemes focus on optimizing network performance under normal conditions, paying little attention to fault tolerance mechanisms after satellite failures, or the mechanisms are too simplistic to handle large-scale cascading scenarios of satellite failures, ultimately leading to rapid failure propagation or even complete network paralysis. To address these issues, this paper proposes a distributed anti-cascading routing scheme based on fuzzy logic, aimed at promptly initiating takeover routing after the network triggers cascading failures, preventing further failure propagation, and restoring the network to stable operation. A strategy for collecting and sharing information of two-hop neighboring satellites is introduced, and a routing decision method based on fuzzy logic is constructed, five main update steps for the membership functions based on a detailed analysis of cascading scenarios. Satellites can make routing decisions to reduce the risk of cascading based on two-hop neighbor information. Compared with six routing schemes under a case constellation, simulation results show that the proposed scheme can ensure stable recovery within 35% satellite failure. The results offering valuable suggestions for network managers.