Network survivability modeling

TitleNetwork survivability modeling
Publication TypeJournal Article
Year of Publication2009
AuthorsPE Heegaard, and KS Trivedi
JournalComputer Networks
Start Page1215
Pagination1215 - 1234
Date Published06/2009

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. © 2009 Elsevier B.V.

Short TitleComputer Networks