Efficient estimation of distance-dependent metrics in edge-failing networks

Efficient estimation of distance-dependent metrics in edge-failing networks

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Article ID: iaor201524329
Volume: 21
Issue: 2
Start Page Number: 199
End Page Number: 213
Publication Date: Mar 2014
Journal: International Transactions in Operational Research
Authors: , , ,
Keywords: simulation: applications
Abstract:

This article introduces a method for estimating performability metrics built upon non‐binary network states, determined by the hop distances between distinguished nodes. The estimation is performed by a Monte Carlo simulation where the sampling space is reduced using edge sets known as d‐pathsets and d‐cutsets. Numerical experiments over two mesh‐like networks are presented. They show significant efficiency improvements relative to the crude Monte Carlo method, in particular as link failures become rarer events, which is usually the case in most real communication networks.

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