共享风险链路组物理长度对光网络可用性影响的蒙特卡罗模拟评价

V. Miletić, B. Mikac, M. Dzanko
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引用次数: 4

摘要

在光网络中,一组逻辑上不同的链路可能无意中共享物理资源(例如,电缆或管道)。这样的组称为共享风险链接组(SRLG),它引入了一种情况,即公共资源的单个故障可能导致多个故障。公共资源的破坏通常是由于物理力量(如挖掘或地震)造成的,并导致多个环节的破坏。具体来说,这种故障可能导致两个边缘节点之间的逻辑连接的工作和备用波长路径同时失效,使它们断开连接,直到完成修复。解决此问题的通常方法包括向网络引入更多的备用容量,以及在计算路径时使用考虑SRLGs的路由算法。这种路由算法避免了创建工作路径对和备用路径对,这些路径对的链路包含在同一个SRLG中,以尽量减少SRLG故障对逻辑连接可用性的负面影响。本文利用蒙特卡罗模拟方法,评估了SRLGs的物理长度对网络可用性的影响。利用离散事件网络模拟器ns-3实现了一种新的可用性评估仿真模型。讨论了模型的实现方法,并概述了模型的特征。对于简单的情况,用该模型得到的蒙特卡罗模拟结果与解析结果进行了比较。一般情况下的可用性的结果是获得使用蒙特卡罗模拟和讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact evaluation of physical length of shared risk link groups on optical network availability using Monte Carlo simulation
In optical networks a group of logically distinct links can unintentionally share a physical resource (e.g, a cable or a duct). Such a group, called shared risk link group (SRLG), introduces a situation where a single failure of common resource can cause multiple failures. Failure of common resource usually occurs due to physical force (e.g, digging or earthquake) and causes failures of multiple links. Specifically, such a failure can cause both working and spare wavelength path of a logical connection between two edge nodes to fail at the same time, leaving them disconnected until a repair is done. The usual approach to solving this problem consists of introducing more spare capacity to the network and also using a routing algorithm that takes SRLGs into account when computing paths. Such a routing algorithm avoids creating working and spare path pairs that have links contained in the same SRLG, to minimize the negative impact of SRLG failure on logical connection availability. In this paper the impact of physical length of the SRLGs on network availability is evaluated using Monte Carlo simulation. New simulation model for availability evaluation is implemented by discrete-event network simulator ns-3. Implementation approach is discussed, and an overview of model features is provided. For simple cases, Monte Carlo simulation results obtained by using the model are compared to analytical results. The availability results for the general case are obtained using Monte Carlo simulation and discussed.
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