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Approach to the Analysis of Probability Measures of Cloud Computing Systems with Dynamic Scaling

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Book cover Distributed Computer and Communication Networks (DCCN 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 601))

Abstract

Cloud computing paradigm proved itself to be a good approach for efficient high-performance computational infrastructure design. Besides performance, one of the most important measures for cloud service providers is energy efficiency of the system. For better energy efficiency, in light load case additional virtual machines are switched off, and switched on again when load increases. Dynamic scaling increases performance of the system, but leads to increase in service costs. To avoid ping-pong effect in dynamic scaling, hysteresis approach is applied. Considering number of virtual machines in modern cloud platforms, special attention should be paid to efficiency of computing algorithm. In this work, we describe behavior of cloud computing system in terms of queuing system with threshold-based hysteretic control of active servers number and noninstantaneous server activation. We use state elimination technique to develop efficient algorithm for stationary probabilities calculations and estimation of its performance measures.

This work was supported in part by the Russian Foundation for Basic Research, projects No. 14-07-00090, 15-07-03051, 15-07-03608.

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References

  1. ETSI Cloud Standards Coordination. Final Report 2013, ver. 1.0. http://www.etsi.org/images/files/Events/2013/2013_CSC_Delivery_WS/CSC-Final_report-013-CSC_Final_report_v1_0_PDF_format-.PDF

  2. Goswami, V., Patra, S.S., Mund, G.B.: Performance analysis of cloud with queue-dependent virtual machines. In: 1st International Conference on Recent Advances in Information Technology, Dhanbad, India, pp. 357–362. IEEE Press (2012)

    Google Scholar 

  3. Pechinkin, A., Gaidamaka, Y., Sopin, E., Talanova, M.: Performance analysis of cloud computing systems with dynamic scaling. In: IX International Annual Scientific and Practical Conference “Modern Information Technologies and IT Education”, pp. 395–406. INTUIT.RU, Moscow (2014)

    Google Scholar 

  4. Shorgin, S.Y., Pechinkin, A.V., Samouylov, K.E., Gaidamaka, Y.V., Gudkova, I.A., Sopin, E.S.: Threshold-based queuing system for performance analysis of cloud computing system with dynamic scaling. In: 12th International Conference of Numerical Analysis and Applied Mathematics ICNAAM-2014, pp. 1–3. AIP Publishing, USA (2015)

    Google Scholar 

  5. Golubchik, L., Lui, J.C.S.: Bounding of performance measures for threshold-based queuing systems: theory and application to dynamic resource management in video-on-demand servers. IEEE Trans. Comput. 51(3), 353–372 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  6. Gaidamaka, Y.V., Pechinkin, A.V., Razumchik, R.V., Samuylov, A.K., Samouylov, K.E., Sokolov, I.A., Sopin, E.S., Shorgin, S.Y.: The distribution of the return time from the set of overload states to the set of normal load states in a system M\(\vert \)M\(\vert \)1|\(<\)L,H\(>\)\(<\)H,R\(>\) with hysteretic load control. Inform. Appl. 7(4), 20–33 (2013)

    Google Scholar 

  7. Basharin, G.P., Gaidamaka, Y.V., Samouylov, K.E.: Mathematical theory of teletraffic and its application to the analysis of multiservice communication of next generation networks. Autom. Control Comput. Sci. 47(2), 62–69 (2013)

    Article  Google Scholar 

  8. Mokrov, E.V., Samouylov, K.E.: Modeling of cloud computing as a queuing system with batch arrivals. T-Comm — Telecommun. Transp. 7(11), 139–141 (2013)

    Google Scholar 

  9. Mokrov, E.V., Chukarin, A.V.: Performance analysis of cloud computing system with live migration. T-Comm — Telecommun. Transp. 8(8), 64–67 (2014)

    Google Scholar 

  10. Gaidamaka, Y., Sopin, E.S., Talanova, M.O.: Performance measures analysis of cloud computing systems with hysteretic control. T-Comm — Telecommun. Transp. 9(9), 54–60 (2015)

    MATH  Google Scholar 

  11. Bocharov, P.P., D’Apice, C., Pechinkin, A.V., Salerno, S.: Queueing Theory. VSP Publishing, Ultrecht, Boston (2004)

    MATH  Google Scholar 

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Acknowledgments

This work was supported in part by the Russian Foundation for Basic Research, projects No. 14-07-00090, 15-07-03051, 15-07-03608.

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Authors and Affiliations

  1. Peoples’ Friendship University of Russia, Miklukho-Maklaya street 6, 117198, Moscow, Russia

    Yuliya Gaidamaka, Eduard Sopin & Margarita Talanova

Authors
  1. Yuliya Gaidamaka
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  2. Eduard Sopin
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  3. Margarita Talanova
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Corresponding author

Correspondence to Eduard Sopin .

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Editors and Affiliations

  1. V.A. Trapeznikov Institute of Control Sc, Russian Academy of Sciences V.A. Trapeznikov Institute of Control Sc, Moscow, Russia

    Vladimir Vishnevsky

  2. V.A. Trapeznikov Inst. of Control Scienc, Russian Academy of Sciences V.A. Trapeznikov Inst. of Control Scienc, Moscow, Russia

    Dmitry Kozyrev

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Gaidamaka, Y., Sopin, E., Talanova, M. (2016). Approach to the Analysis of Probability Measures of Cloud Computing Systems with Dynamic Scaling. In: Vishnevsky, V., Kozyrev, D. (eds) Distributed Computer and Communication Networks. DCCN 2015. Communications in Computer and Information Science, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-319-30843-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-30843-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30842-5

  • Online ISBN: 978-3-319-30843-2

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