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Modeling and Fuzzy Availability Analysis of Computer Networks: A Case Study

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Information and Communication Technology for Intelligent Systems ( ICTIS 2020)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 195))

Abstract

The traditional theory of reliability is based on the Bernoulli trials, i.e., either success or failure. However, it seems unrealistic for enormous complex systems like computer networks. To overcome this issue, in the present study, an effort has been made regarding the development of a mathematical model for a computer network system and analysis of fuzzy availability of the same. The concepts of constant failure, constant repair, and coverage factor have been used for the development of the model. Impact of coverage factor, repair rates and failure rates of components has been analyzed on fuzzy availability of system. Markov birth-death process has been used for the development of Chapman-Kolmogorov differential-difference equations. The leading differential equations have been simplified by Runge–Kutta method of order four employing MATLAB (Ode 45 function).

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India

    Ashish Kumar, Ombir Dahiya & Monika Saini

Authors
  1. Ashish Kumar
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  2. Ombir Dahiya
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  3. Monika Saini
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Corresponding author

Correspondence to Ashish Kumar .

Editor information

Editors and Affiliations

  1. Department of Electrical and Electronics Engineering, University of the Ryukyus, Nishihara, Japan

    Tomonobu Senjyu

  2. Sinhgad Technical Education Society, SKNCOE, Pune, India

    Parikshit N. Mahalle

  3. Universiti Putra Malaysia, Serdang, Malaysia

    Thinagaran Perumal

  4. Global Knowledge Research Foundation, Ahmedabad, India

    Amit Joshi

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Kumar, A., Dahiya, O., Saini, M. (2021). Modeling and Fuzzy Availability Analysis of Computer Networks: A Case Study. In: Senjyu, T., Mahalle, P.N., Perumal, T., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems. ICTIS 2020. Smart Innovation, Systems and Technologies, vol 195. Springer, Singapore. https://doi.org/10.1007/978-981-15-7078-0_1

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