Forecasting of component failures and service availability

Phaneendra Magapu, Sai Priya Vissapragada Vissapragada

Abstract


When a segment of a basic interchange’s administration falls flat, how pressing is a fix on the off chance that we fix inside 60 minutes, 2 hours or n hours, how does this influence the likelihood of administration disappointment? Could a conventional model help the effect, prioritization and arranging of fixes in case of segment disappointment and anticipate support costs? These are a portion of the inquiries that an enormous association pose to us and we report here our involvement with building up a stochastic structure dependent on a discrete spatial model and a fleeting rationale to reply. We characterize and investigate fixed and transitional standard worldly coherent properties for the likelihood of disappointment of the administration inside certain time limits, we predict the support expenses and we present another idea of transport inclusion that evaluate the impact of the condition of the parts of the lower segments. on the accessibility of the administration. The subsequent model is profoundly defined and a light electronic interface bolsters client cooperation for tests.


References


C. Baier, B. R. Haverkort, H. Hermanns, and J.-P. Katoen, “ModelChecking Algorithms for Continuous-Time Markov Chains,” IEEE Trans. Software Eng., vol. 29, no. 6, pp. 524–541, 2003.

M. Kwiatkowska, G. Norman, and D. Parker, “Stochastic model checking,” in Formal Methods for the Design of Computer, Communication and Software Systems: Performance Evaluation (SFM’07), 2007.

——, “PRISM 4.0: Verification of probabilistic real-time systems,” in Proc. 23rd International Conference on Computer Aided Verification (CAV’11), ser. LNCS, vol. 6806. Springer, 2011, pp. 585–591.

W. Bux and U. Herzog, “The phase concept: Approximation of measured data and performance analysis,” Computer Performance, pp. 23–38, 1977.

L. Cloth and B. R. Haverkort, “Model checking for survivability!” in Quantitative Evaluation of Systems, 2005. Second International Conference on the, Sept 2005, pp. 145–154.

M. Sevegnani and M. Calder, “Bigraphs with sharing,” Theoretical Computer Science, vol. 577, p. 43 74, 2015.

J.-P. Katoen, “The Probabilistic Model Checking Landscape,” LICS16 (Logics in Computer Science), 2016.

S. Garg, A. Puliafito, M. Telek, and K. Trivedi, “Analysis of software rejuvenation using markov regenerative stochastic petri net,” in Software Reliability Engineering, 1995. Proceedings., Sixth International Symposium on, 1995, pp. 180–187.

R. Pyke, “Markov renewal processes: definitions and preliminary properties,” The Annals of Mathematical Statistics, pp. 1231–1242, 1961.

D. M. Nicol, W. H. Sanders, and K. S. Trivedi, “Model-based evaluation: from dependability to security,” Dependable and Secure Computing, IEEE Transactions on, vol. 1, no. 1, pp. 48–65, 2004.


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