发表机构
Orange Research; Ecole Polytechnique（Orange Research; 巴黎综合理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对核心IP/MPLS网络中的多周期维护问题，提出T-ASR优化模型，通过字典序目标最小化链路负载排序向量，并采用两种MILP公式（ALEXA和STELA）分解求解，在中小型网络上验证了效率。
AI 中文摘要
本文提出了一个源于核心IP/MPLS网络流量工程的多周期优化问题，称为T-ASR。该问题旨在计算一系列段路由路径，以适应多周期计划维护，同时允许连续时间步之间有限数量的路径重配置。我们不仅关注最小化经典的最大链路利用率（MLU）标准，还引入了一种更精细的字典序目标，该目标最小化整个链路负载排序向量，从而为所有链路提供更高效的资源利用。我们提出了一种通用方法，将这一问题分解为一系列子问题。为了对每个子问题建模，我们引入了两种混合整数线性规划（MILP）公式，即ALEXA和STELA，从而形成我们方法的两个变体。最后，我们在中小型网络实例上评估并比较了这两种变体的效率。
英文摘要
In this paper, we present a multi-period optimization problem arising from the traffic engineering of core IP/MPLS networks, called T-ASR. This problem aims at computing a sequence of segment routing paths that adapt to a multi-period scheduled maintenance, while allowing limited number of path reconfigurations between successive time steps. Rather than focusing solely on minimizing the classical Maximum Link Utilization (MLU) criteria, we introduce a more refined lexicographic objective that minimizes the entire sorted vector of link loads providing a more efficient resource utilization for all the links. We propose a generic approach that decomposes this problem into a sequence of subproblems. To model each subproblem, we introduce two Mixed Integer Linear Programming (MILP) formulations, ALEXA and STELA, resulting in two variants of our approach. Finally, we evaluate and compare the efficiency of both variants on small to medium-sized network instances.
Comments9 pages, 3 figures
