Efficient parametric analysis of performance measures for communication networks

Efficient techniques for estimating performance measures in communication networks in a steady-state or transient setting are developed. These techniques may be used in a simulation environment or in connection with real-time observations. For Markov chain models, the recently proposed standard clock approach is extended, and a class of real-time algorithms for simultaneously generating multiple sample paths under different parameter sets is presented. Attention is focused on the link crash time estimation problem, where a 'crash' is defined as the first time a buffer overflows, given some initial conditions. An algorithm for estimating crash times under various traffic shocks is derived, where all estimates are obtained in parallel to an actual network's normal operation. An algorithm for crash time estimation of a G/D/1 link model is also derived using a different (perturbation-analysis-based) approach. Finally, extensive simulation results are provided to validate the proposed algorithms and compare them to brute-force simulation.