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Reconfiguration of spare capacity for MPLS-based recovery in the Internet backbone networks

机译:重新配置备用容量以在Internet主干网中进行基于MPLS的恢复

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This paper introduces a novel approach, called Short Leap Shared Protection with spare capacity Reallocation (SLSP-R), to deal with dynamic reconfiguration of spare capacity for MPLS-based recovery in the Internet backbone networks. SLSP-R is based on the SLSP framework and is designed to quantify the impact of computation complexity on network performance. The basic idea for SLSP-R is to subdivide a lengthy optimization process into several subtasks in order to trade the optimization quality with computation time. For this purpose, we compare three strategies for grouping working paths before an integer programming (InP) formulation is solved, namely, the Most Overlapped, Most Diverse, and Randomly Distributed. Analytical modeling of the problem is provided to show the feasibility of the subgrouping strategy. A numerical experiment as well as simulation-based study are conducted on four networks with different topology to evaluate the SLSP-R algorithm. The design methodology to determine the size of each subset of working paths is verified in the simulation.
机译:本文介绍一种新颖的方法,称为“带有备用容量重新分配的短跳共享保护”(SLSP-R),用于处理备用容量的动态重新配置,以实现Internet骨干网中基于MPLS的恢复。 SLSP-R基于SLSP框架,旨在量化计算复杂性对网络性能的影响。 SLSP-R的基本思想是将冗长的优化过程细分为几个子任务,以便将优化质量与计算时间进行权衡。为此,我们比较了在求解整数编程(InP)公式之前对工作路径进行分组的三种策略,即“最重叠”,“最多样化”和“随机分布”。提供了问题的分析模型,以显示分组策略的可行性。在具有不同拓扑的四个网络上进行了数值实验和基于仿真的研究,以评估SLSP-R算法。仿真中验证了确定工作路径每个子集大小的设计方法。

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