Accelerated reliability analysis for self-healing SONET networks

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Accelerated reliability analysis for self-healing SONET networks

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Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication table of contents

Vancouver, British Columbia, Canada

Pages: 268 - 277

Year of Publication: 1998

ISBN:1-58113-003-1

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Authors

Hakki C. Cankaya	Department of Computer Science and Engineering, Southern Methodist University, Dallas, TX
V. S. S. Nair	Department of Computer Science and Engineering, Southern Methodist University, Dallas, TX

Sponsor

SIGCOMM: ACM Special Interest Group on Data Communication

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 13, Downloads (12 Months): 34, Citation Count: 0

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ABSTRACT

Recently, a parametric State Reward Markov Model (SRMM/p) has been developed for the reliability and availability analysis of self-healing SONET mesh networks [2]. In this paper, we investigate the factors that affect the run-time complexity of the model presented in [2]. In order to accelerate the reliability and availability analysis, we present an approach that aggregates a set of states in the model based on 2-phase hypoexponential distribution. A comparison of the original and the reduced model, with respect to runtime complexity and accuracy, is carried out by applying the models for the analysis of few complex networks.

REFERENCES

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