# Fast Reroute Mechanism for Satellite Networks Based on Segment Routing and Dual Timers Switching
## 2 Related Work  
Current rerouting strategies are generally classified into passive and active rerouting [8; 9]. Passive rerouting relies on Interior Gateway Protocols (IGPs) to achieve network convergence after a failure [10; 11]; however, during the convergence period, traffic cannot be rerouted promptly. In contrast, active rerouting involves precomputing backup paths and swiftly redirecting traffic to these alternative routes upon the detection of link failures. Nonetheless, active rerouting faces significant challenges, particularly related to the limitations of localized fault detection at network nodes and the asynchronous nature of network state updates [12; 13]. These issues can potentially lead to routing instability, such as the formation of routing loops. To optimize rerouting strategies and enhance the stability and efficiency of terrestrial networks, numerous classical solutions have been developed in this field. In [14], a fast rerouting (FRR) method is proposed, wherein a Point of Local Repair (PLR) reroutes traffic to precomputed Loop-Free Alternates (LFAs) when a failure occurs in protected components, such as links or nodes. However, in certain topologies, the PLR may be unable to find an LFA for specific destinations, leading to the absence of backup paths. In [15], the concept of Remote LFA (RLFA) is introduced, utilizing Multiprotocol Label Switching (MPLS) to direct data to a remote node, bypassing the PLR. While RLFA addresses some of the limitations of the LFA approach, it does not guarantee complete coverage due to challenges in selecting appropriate remote nodes. In [16], the TI-LFA, which is based on segment routing, is proposed to overcome the limitations of RLFA. This method prevents loops by encoding the backup path as a segment list, enabling rerouting in scenarios where conventional paths could lead to loops. Building upon the classical rerouting strategies, some scholars have proposed rerouting strategies specifically suited for satellite networks. In [7], an innovative FRR algorithm for Low-Earth-Orbit (LEO) satellite networks with relay satellites is presented. This algorithm combines centralized and distributed routing strategies to facilitate efficient backup path updates without requiring full recalculations. However, it faces challenges in topology design, such as the need for the careful planning of relay satellite placements and clearly defining the roles of satellites responsible for calculation and forwarding. In [17], a solution to the issues of traffic imbalance and rapid failure recovery in ground station-assisted Low-Earth Orbit (LEO) satellite constellations is proposed. The DBTS/DBTS+ traffic allocation algorithm and the LFA/LFA+ fast rerouting mechanism are introduced. DBTS+ reduces the maximum satellite load by 30% by prioritizing traffic allocation to shorter paths, with only a 10% increase in delay. LFA+ improves the protection coverage by approximately 15% by employing two backup paths. In [18], a satellite-customized segment routing protocol (STSR) is introduced to address the low bandwidth efficiency of segment routing in satellite resource-constrained environments. Using bitmap encoding (SBE) and the path unwrapping mechanism (BUM), the protocol reduces the routing header size by 43.51% (with a 2000-satellite scale) compared to SRv6, achieving a bandwidth efficiency improvement of 43% to 92%. In [19], a geo-vector-based segment routing method is proposed to mitigate the issues of load imbalance and frequent topology changes in multilayer satellite networks. Through dynamic routing table maintenance strategies (time/state hybrid trigger updates) and regional hierarchical management, the impact of the satellite movement is mitigated. The end-to-end delay is reduced to near theoretical values, while the throughput is increased by 5% in high-load scenarios. Finally, ref. [20] introduces a priority-based rerouting method that calculates link redundancy and selects backup paths based on a minimal interference algorithm.