基于时间重构约束的段路由流量工程
Segment Routing Traffic Engineering with Time-Based Reconfiguration Constraints
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中文总结 AI 辅助
针对IP/MPLS网络中链路故障下的段路由流量工程，提出带重构预算的MLU列生成优化框架，在真实大规模拓扑上实现低于5%的最优性差距。
中文摘要 AI 辅助
段路由（SR）涉及通过最短路径或有限数量的段来路由请求，这些段本身是其端点之间的最短路径。虽然这种灵活性使得段路由在IP/MPLS网络的流量工程（TE）中具有吸引力，但当某些链路不可用（例如，维护）且路由决策必须适应同时限制两个连续时段之间的配置更改数量时，更新变得具有挑战性。我们解决了为多个流量需求动态选择SR-TE配置的问题，目标是最小化最大链路利用率（MLU）。此外，施加了重构预算以限制修改的段数量。基于此表示，我们开发了一个MLU列生成优化框架。它允许在时变IP/MPLS网络中联合考虑流量分布、SR配置复杂性和时间重构成本。数值结果使用Orange提供的真实数据集获得，拓扑包含多达1,263个节点和15,000个流量需求。在133个实例-时间评估中，80.45%的最优性差距（即准确性）低于5%。
英文摘要
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.
发表机构
- Concordia University（康科迪亚大学）
机构由 AI 辅助整理，请以论文原文为准。
