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An analytical modeling framework to evaluate converged networks through business-oriented metrics

Author

Listed:
  • Guimarães, Almir P.
  • Maciel, Paulo R.M.
  • Matias, Rivalino

Abstract

Nowadays, society has increasingly relied on convergent networks as an essential means for individuals, businesses, and governments. Strategies, methods, models and techniques for preventing and handling hardware or software failures as well as avoiding performance degradation are, thus, fundamental for prevailing in business. Issues such as operational costs, revenues and the respective relationship to key performance and dependability metrics are central for defining the required system infrastructure. Our work aims to provide system performance and dependability models for supporting optimization of infrastructure design, aimed at business oriented metrics. In addition, a methodology is also adopted to support both the modeling and the evaluation process. The results showed that the proposed methodology can significantly reduce the complexity of infrastructure design as well as improve the relationship between business and infrastructure aspects.

Suggested Citation

  • Guimarães, Almir P. & Maciel, Paulo R.M. & Matias, Rivalino, 2013. "An analytical modeling framework to evaluate converged networks through business-oriented metrics," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 81-92.
  • Handle: RePEc:eee:reensy:v:118:y:2013:i:c:p:81-92
    DOI: 10.1016/j.ress.2013.04.008
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    References listed on IDEAS

    as
    1. Ramirez-Marquez, José Emmanuel & Rocco, Claudio M., 2008. "All-terminal network reliability optimization via probabilistic solution discovery," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1689-1697.
    2. Cao, Dingzhou & Murat, Alper & Chinnam, Ratna Babu, 2013. "Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 154-163.
    3. Cook, Jason L. & Ramirez-Marquez, Jose Emmanuel, 2009. "Optimal design of cluster-based ad-hoc networks using probabilistic solution discovery," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 218-228.
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