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Network survivability modeling

  • Norwegian University of Science and Technology
  • Duke University

Research output: Contribution to journalArticlepeer-review

161 Scopus citations

Abstract

Critical services in a telecommunication network should be continuously provided even when undesirable events like sabotage, natural disasters, or network failures happen. It is essential to provide virtual connections between peering nodes with certain performance guarantees such as minimum throughput, maximum delay or loss. The design, construction and management of virtual connections, network infrastructures and service platforms aim at meeting such requirements. In this paper we consider the network's ability to survive major and minor failures in network infrastructure and service platforms that are caused by undesired events that might be external or internal. Survive means that the services provided comply with the requirement also in presence of failures. The network survivability is quantified as defined by the ANSI T1A1.2 committee which is the transient performance from the instant an undesirable event occurs until steady state with an acceptable performance level is attained. The assessment of the survivability of a network with virtual connections exposed to link or node failures is addressed in this paper. We have developed both simulation and analytic models to cross-validate our assumptions. In order to avoid state space explosion while addressing large networks we decompose our models first in space by studying the nodes independently and then in time by decoupling our analytic performance and recovery models which gives us a closed form solution. The modeling approaches are applied to both small and real-sized network examples. Three different scenarios have been defined, including single link failure, hurricane disaster, and instabilities in a large block of the system (transient common failure). The results show very good correspondence between the transient loss and delay performance in our simulations and in the analytic approximations.

Original languageEnglish
Pages (from-to)1215-1234
Number of pages20
JournalComputer Networks
Volume53
Issue number8
DOIs
StatePublished - 11 Jun 2009
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Analytical models
  • End-to-end performance
  • Simulation
  • Survivability

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