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Availability Modeling and Evaluation of a Network Service Deployed via NFV

  • Mario Di MauroEmail author
  • Maurizio Longo
  • Fabio Postiglione
  • Marco Tambasco
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 766)

Abstract

The Network Function Virtualization (NFV) has been conceived as an enabler of novel network infrastructures and services that can be deployed by combining virtualized network elements. In particular, NFV is suited to boost the deployment flexibility of Service Function Chains (SFCs). In this paper, we address an availability evaluation of a chain of network nodes implementing a SFC managed by the Virtualized Infrastructure Manager (VIM), responsible for handling and controlling the system resources. A double-layer model is adopted, where Reliability Block Diagram describes the high-level dependencies among the architecture components, and Stochastic Reward Networks model the probabilistic behavior of each component. In particular, a steady-state availability analysis is carried out to characterize the minimal configuration of the overall system guaranteeing the so-called “five nines” requirement, along with a sensitivity analysis to evaluate the system robustness with respect to variations of some key parameters.

Keywords

Network function virtualization Service function chaining Stochastic reward nets Reliability block diagram Availability analysis 

References

  1. 1.
    ETSI: Network functions virtualisation: an introduction, benefits, enablers, challenges and call for action. Technical report (2012)Google Scholar
  2. 2.
    Medhat, A.M., Taleb, T., Elmangoush, A., Carella, G.A., Covaci, S., Magedanz, T.: Service function chaining in next generation networks: state of the art and research challenges. IEEE Commun. Mag. 55(2), 216–223 (2017)CrossRefGoogle Scholar
  3. 3.
    Taleb, T., Ksentini, A., Sericola, B.: On service resilience in cloud-native 5g mobile systems. IEEE J. Sel. Areas Commun. 34(3), 483–496 (2016)CrossRefGoogle Scholar
  4. 4.
    ETSI: Network Functions Virtualisation (NFV) reliability; report on models and features for end-to-end reliability. Technical report (2016)Google Scholar
  5. 5.
    Yamato, Y., Nishizawa, Y., Nagao, S., Sato, K.: Fast and reliable restoration method of virtual resources on OpenStack. IEEE Trans. Cloud Comput. (in press, 2015)Google Scholar
  6. 6.
    Khazaei, H., Mii, J., Mii, V.B., Mohammadi, N.B.: Availability analysis of cloud computing centers. In: 2012 IEEE Global Communications Conference (GLOBECOM), pp. 1957–1962 (2012)Google Scholar
  7. 7.
    Zhang, X., Lin, C., Kong, X.: Model-driven dependability analysis of virtualization systems. In: 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science, pp. 199–204 (2009)Google Scholar
  8. 8.
    Dantas, J., Matos, R., Araujo, J., Maciel, P.: An availability model for eucalyptus platform: an analysis of warm-standy replication mechanism. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics, pp. 1664–1669 (2012)Google Scholar
  9. 9.
    Di Mauro, M., Postiglione, F., Longo, M.: Reliability analysis of the controller architecture in software defined networks. In: Podofillini, L., Sudret, B., Stojadinovic, E., Zio, B., Kröger, W. (eds.) Safety and Reliability of Complex Engineered Systems, pp. 1503–1510. Taylor & Francis Group (2015)Google Scholar
  10. 10.
    Di Mauro, M., Postiglione, F., Longo, M., Restaino, R., Tambasco, M.: Availability evaluation of the virtualized infrastructure manager in Network Function Virtualization environments. In: Walls, L., Revie, M., Bedford, T. (eds.) Risk, Reliability and Safety: Innovating Theory and Practice, pp. 2591–2596. Taylor & Francis Group (2017Google Scholar
  11. 11.
    Di Mauro, M., Longo, M., Postiglione, F.: Performability evaluation of software defined networking infrastructures. In: ValueTools 2016–10th EAI International Conference on Performance Evaluation Methodologies and Tools, pp. 1–8 (2016)Google Scholar
  12. 12.
    Kuo, W., Ming, Z., Modeling, O.R.: Principles and Applications. Wiley, New York (2002)Google Scholar
  13. 13.
    Muppala, J.K., Ciardo, G., Trivedi, K.S.: Stochastic Reward Nets for reliability prediction. In: Communications in Reliability, Maintainability and Serviceability, pp. 9–20 (1994)Google Scholar
  14. 14.
    Nicol, D.M., Sanders, W.H., Trivedi, K.S.: Model-based evaluation: from dependability to security. IEEE Trans. Depend. Sec. Comput. 1(1), 48–65 (2004)CrossRefGoogle Scholar
  15. 15.
    Muppala, J.K., Malhotra, M., Trivedi, K.S.: Markov Dependability Models of Complex Systems: Analysis Techniques. Springer, Berlin Heidelberg (1996)zbMATHGoogle Scholar
  16. 16.
    de Matos, R., Maciel, S., Machida, P., Dong, F., Seong, K., Trivedi, K.: Sensitivity analysis of server virtualized system availability. IEEE Trans. Rel. 61(4), 994–1006 (2012)CrossRefGoogle Scholar
  17. 17.
    Sahner, R.A., Trivedi, K.S.: Reliability modeling using SHARPE. IEEE Trans. Rel. 36(2), 186–193 (1987)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mario Di Mauro
    • 1
    Email author
  • Maurizio Longo
    • 1
  • Fabio Postiglione
    • 1
  • Marco Tambasco
    • 2
  1. 1.Department of Information and Electrical Engineering and Applied Mathematics (DIEM)University of SalernoFiscianoItaly
  2. 2.Research Consortium on Telecommunications (CoRiTeL)FiscianoItaly

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