Segment Routing Traffic Engineering with Time-Based Reconfiguration Constraints

2026-10-03

AI Summary

This study addresses the challenge of dynamically updating time-constrained segment routing traffic engineering in IP/MPLS networks by proposing a column generation optimization framework that accounts for temporal reconfiguration costs. Under configuration change budget constraints, the proposed method jointly optimizes traffic distribution and segment routing complexity to minimize maximum link utilization. It integrates column generation algorithms with integer programming techniques to efficiently solve large-scale network problems. Experimental evaluations on real-world datasets from Orange demonstrate that 80.45% of the test instances achieve an optimality gap below 5%, effectively balancing network performance with configuration stability.

Abstract

Segment routing (SR) involves routing requests through shortest paths or a limited number of segments, which are themselves the shortest paths between their endpoints. While this flexibility makes segment routing attractive for traffic engineering (TE) in IP/MPLS networks, it becomes challenging to update when some links become unavailable (e.g., maintenance) and routing decisions must adapt while limiting the number of configuration changes between two consecutive periods. We address the problem of dynamically selecting SR-TE configurations for multiple traffic demands with the objective of minimizing the maximum link utilization (MLU). In addition, a reconfiguration budget is imposed in order to limit the number of segments modified. Based on this representation, we develop a MLU column-generation optimization framework. It allows to jointly consider traffic distribution, SR configuration complexity, and temporal reconfiguration costs in time-varying IP/MPLS networks. The numerical results are obtained using realistic datasets provided by Orange, with topologies containing up to 1,263 nodes and 15,000 traffic demands. The optimality gap (i.e., accuracy) is below 5% in 80.45% of the 133 instance-time evaluations.

Problem

• Segment Routing
• Traffic Engineering
• Reconfiguration Constraints
• Maximum Link Utilization
• IP/MPLS Networks

Innovation

• Segment Routing
• Traffic Engineering
• Column Generation
• Reconfiguration Constraints
• Maximum Link Utilization