Modeling and analyzing the performance of adaptive hierarchical networks

As networks become larger, scalability and QoS-awareness become important issues that have to be resolved. A large network can be effectively formed as a hierarchical structure, such as the inter/intra-domain routing hierarchy in the Internet and the Private Network-to-Network Interface (PNNI) standard, to resolve these critical issues. Methods of modeling and analyzing the performance of QoS-capable hierarchical networks become an open issue. Although the reduced load approximation technique has been extensively applied to flat networks, the feasibility of applying it to the hierarchical network model has seldom been investigated. Furthermore, most of the research in this area has focused on the performance evaluation with fixed routing. This work proposes an analytical model for evaluating the performance of adaptive hierarchical networks with multiple classes of traffic. We first study the reduced load approximation model for multirate loss networks, and then propose a novel performance evaluation model for networks with hierarchical routing. This model is based on a decomposition of a hierarchical route into several analytic hierarchical segments; therefore the blocking probability of the hierarchical path can be determined from the blocking probabilities of these segments. Numerical results demonstrate that the proposed model for adaptive hierarchical routing yields accurate blocking probabilities. We also investigate the convergence of the analysis model in both the originating-destination (O-D) pair and the alternative hierarchical path. Finally, the blocking probability of the adaptive hierarchical O-D pair is demonstrated to depend on the blocking of all hierarchical paths but not on the order of the hierarchical path of the same O-D pair.