Performance analysis for hierarchical multirate loss networks

  • Authors:
  • Ben-Jye Chang;Ren-Hung Hwang

  • Affiliations:
  • Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung 413, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi 621, Taiwan, R.O.C.

  • Venue:
  • IEEE/ACM Transactions on Networking (TON)
  • Year:
  • 2004

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Abstract

The reduced load approximation technique has been extensively applied to flat networks, but the feasibility of applying it to hierarchical network model has seldom been described. Hierarchical routing is essential for large networks such as the Internet inter/intra-domain routing hierarchy and the Private Network to Node Interface (PNNI) standard. Therefore, this paper proposes an efficient and accurate analytical model for evaluating the performance of hierarchical networks with multiple classes of traffic. A performance analysis model with considering multiple classes of traffic, the complexity of analytical and explosion of computation will be extremely increased, and hence, result in inaccurate analytical. The issue of multiple classes of traffic has to be addressed in performance analysis model. In this paper, we first study the reduced load approximation model for loss networks, and then propose a novel performance evaluation model for large networks with multirate hierarchical routing. The hierarchical evaluation model is based on decomposing a hierarchical route into several analytic hierarchical segments. Once the blockings of these hierarchical segments are accurately determined, the blocking of the hierarchical path can be estimated accurately from these segments blocking. Numerical results indicate that the proposed hierarchical reduced load approximation yields quite accurate blocking probabilities as compared to that of simulation results. Furthermore, the accuracy of the proposed hierarchical reduced load approximation heuristic is independent of the blocking or the offered traffic load. Finally, we also draw some remarks on the convergence of the reduced load based approximation analysis model.