Critical services in a telecommunication network should survive and be continuously provided even when undesirable events like sabotage, natural disasters, or network failures happen. 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. Performance guarantees such as minimum throughput, maximum delay or loss should be considered.   This paper demonstrates alternative modeling approaches to quantify network survivability, including stochastic reward nets and continuous time Markov chain models, and cross-validates these with a process-oriented simulation model. The experience with these modeling approaches applied to networks of different sizes clearly demonstrates the trade-offs that need to be considered with respect to flexibility in changing and extending the model, model abstraction and readability, and scalability and complexity of the solution method.
['Poul E. Heegaard', 'Kishor S. Trivedi']
Survivability modeling with stochastic reward nets