Skip to main content
Log in

A stochastic reward net-based assessment of reliability, availability and operational cost for a software-defined network infrastructure

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The networking infrastructure of a software-defined network (SDN) requires further study to achieve continuity and high availability of data transactions for cloud computing services. However, various types of failures on links or system components are encountered because of high-speed and complicated structures of hosts and network devices. This study examines the specific characteristics and impact of various failures on a typical SDN infrastructure. We propose a stochastic model using stochastic reward net by incorporating hardware failures (of hosts, switches, storage, and links) and software failures [virtual machines (VMs)]. The system model is analyzed based on steady-state availability under default parameters. Comprehensive sensitivity analyses are conducted to study the system behaviors with respect to different major factors of impact. A reliability analysis is also conducted to pinpoint the role of VM migration in extending the system lifetime. Furthermore, operational cost is analyzed in detail to identify the main sources and to observe the effect of major system parameters on costs over time. The analytical results are verified by a developed discrete-event simulation module based on CloudSim Plus simulation open-source package. This study provides a helpful basis for network design and implementation in SDN infrastructures.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Hu F, Hao Q, Bao K (2014) A survey on software-defined network and openflow: from concept to implementation. IEEE Commun Surv Tutor 16(4):2181–2206. https://doi.org/10.1109/COMST.2014.2326417

    Article  Google Scholar 

  2. Cui Y, Xiao S, Liao C, Stojmenovic I, Li M (2013) Data centers as software defined networks: traffic redundancy elimination with wireless cards at routers. IEEE J Sel Areas Commun 31(12):2658–2672. https://doi.org/10.1109/JSAC.2013.131207

    Article  Google Scholar 

  3. Nguyen TA, Kim DS, Park JS (2014) A comprehensive availability modeling and analysis of a virtualized servers system using stochastic reward nets. Sci World J 2014:1–18. https://doi.org/10.1155/2014/165316

    Google Scholar 

  4. Nguyen TA, Min D, Choi E (2017) A comprehensive evaluation of availability and operational cost for a virtualized server system using stochastic reward nets. J Supercomput 74:1–55. https://doi.org/10.1007/s11227-017-2127-2

    Google Scholar 

  5. Nguyen TA, Kim DS, Park JS (2016) Availability modeling and analysis of a data center for disaster tolerance. Future Gener Comput Syst 56:27–50. https://doi.org/10.1016/j.future.2015.08.017

    Article  Google Scholar 

  6. Huh J-H, Seo K (2016) Design and test bed experiments of server operation system using virtualization technology. Hum Centric Comput Inf Sci 6(1):1. https://doi.org/10.1186/s13673-016-0060-7

    Article  Google Scholar 

  7. Thorpe S (2012) Virtual machine history model framework for a data cloud digital investigation. J Converg 3(4):9–14

    Google Scholar 

  8. Drutskoy D, Keller E, Rexford J (2013) Scalable network virtualization in software-defined networks. IEEE Internet Comput 17(2):20–27. https://doi.org/10.1109/MIC.2012.144

    Article  Google Scholar 

  9. Vaghani R, Lung C-H (2014) A comparison of data forwarding schemes for network resiliency in software defined networking. Procedia Comput Sci 34:680–685. https://doi.org/10.1016/j.procs.2014.07.097

    Article  Google Scholar 

  10. Kreutz D, Ramos FM, Verissimo P (2013) Towards secure and dependable software-defined networks, In: Proceedings of the Second ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking, p 55. https://doi.org/10.1145/2491185.2491199

  11. Kuklinski SS, Chemouil P (2014) Network management challenges in software-defined networks. IEICE Trans Commun E97–B(1):2–9

    Article  Google Scholar 

  12. Li H, Li P, Guo S, Nayak A (2014) Byzantine-resilient secure software-defined networks with multiple controllers in cloud. IEEE Trans Cloud Comput 2(4):436–447. https://doi.org/10.1109/TCC.2014.2355227

    Article  Google Scholar 

  13. van Adrichem NLM, van Asten BJ, Kuipers FA (2014) Fast recovery in software-defined networks. In: 2014 Third European Workshop on Software Defined Networks. IEEE, pp 61–66. https://doi.org/10.1109/EWSDN.2014.13 ISBN: 978-1-4799-6919-7

  14. Yao G, Bi J, Guo L (2013) On the cascading failures of multi-controllers in software defined networks. In: 2013 21st IEEE International Conference on Network Protocols (ICNP). IEEE, pp 1–2. https://doi.org/10.1109/ICNP.2013.6733624 ISBN: 978-1- 4799-1270-4

  15. Gelberger A, Yemini N, Giladi R (2013) Performance analysis of software-defined networking (SDN). In: 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems. IEEE, pp 389–393. https://doi.org/10.1109/MASCOTS.2013.58 ISBN: 978-0-7695-5102-9

  16. Longo F, Distefano S, Bruneo D, Scarpa M (2015) Dependability modeling of software defined networking. Comput Netw 83:280–296. https://doi.org/10.1016/j.comnet.2015.03.018

    Article  Google Scholar 

  17. Malkawi MI (2013) The art of software systems development: reliability, availability, maintainability, performance (RAMP). Hum Centric Comput Inf Sci 3(1):22. https://doi.org/10.1186/2192-1962-3-22

    Article  Google Scholar 

  18. Filho MCS, Oliveira RL, Monteiro CC, Inacio PRM, Freire MM (2017) CloudSim plus: a cloud computing simulation framework pursuing software engineering principles for improved modularity, extensibility and correctness. In: 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). IEEE, pp 400–406. https://doi.org/10.23919/INM.2017.7987304 ISBN: 978-3-901882-89-0

  19. Calheiros RN, Ranjan R, De Rose CAF, Buyya R (2009) CloudSim: a novel framework for modeling and simulation of cloud computing infrastructures and services. arXiv:0903.2525

  20. Goyal T, Singh A, Agrawal A (2012) Cloudsim: simulator for cloud computing infrastructure and modeling. Procedia Eng 38:3566–3572. https://doi.org/10.1016/j.proeng.2012.06.412

    Article  Google Scholar 

  21. Calheiros RN, Ranjan R, Beloglazov A, De Rose CAF, Buyya R (2011) CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw Pract Exp 41(1):23–50. https://doi.org/10.1002/spe.995

    Article  Google Scholar 

  22. Mehmi S, Verma HK, Sangal A (2017) Simulation modeling of cloud computing for smart grid using CloudSim. J Electr Syst Inf Technol 4(1):159–172. https://doi.org/10.1016/j.jesit.2016.10.004

    Google Scholar 

  23. Shiraz M, Gani A (2012) Mobile cloud computing: critical analysis of application deployment in virtual machines. In: International Conference on Information and Computer Networks ICICN 2012, vol 27. IACSIT Press, Singapore, pp 11–16

  24. Bruneo D, Lhoas A, Longo F, Puliafito A (2014) Modeling and evaluation of energy policies in green clouds. IEEE Trans Parallel Distrib Syst PP(99):1–1. https://doi.org/10.1109/TPDS.2014.2364194

    Google Scholar 

  25. Kreutz D, Ramos FMV, Verissimo P, Rothenberg CE, Azodolmolky S, Uhlig S (2014) Software-defined networking: a comprehensive survey. CoRR, vol abs/1406.0, p 49. arXiv:1406.0440

  26. Xia W, Wen Y, Foh C, Niyato D, Xie H (2014) A survey on software-defined networking. IEEE Commun Surv Tutor PP(99):1–1. https://doi.org/10.1109/COMST.2014.2330903

    Google Scholar 

  27. Xie J, Guo D, Hu Z, Qu T, Lv P (2015) Control plane of software defined networks: a survey. Comput Commun 67:1–10. https://doi.org/10.1016/j.comcom.2015.06.004

    Article  Google Scholar 

  28. Farhady H, Lee H, Nakao A (2015) Software-defined networking: a survey. Comput Netw 81:79–95. https://doi.org/10.1016/j.comnet.2015.02.014

    Article  Google Scholar 

  29. Matos RDS, Maciel PRM, Machida F, Kim DS, Trivedi KS (2012) Sensitivity analysis of server virtualized system availability. IEEE Trans Reliab 61(4):994–1006. https://doi.org/10.1109/TR.2012.2220711

    Article  Google Scholar 

  30. Strunk A, Dargie W (2013) Does live migration of virtual machines cost energy? In: 2013 IEEE 27th International Conference on 2013, pp 514–521. https://doi.org/10.1109/AINA.2013.137

  31. Strunk A (2012) Costs of virtual machine live migration: a survey. In: 2012 IEEE Eighth World Congress on Services. IEEE, 2012, pp 323–329. https://doi.org/10.1109/SERVICES.2012.23 ISBN: 978-1-4673-3053-4

  32. Huang C, Chen J, Zhang L, Zhu Q (2013) Architecting dependable virtual computing system with considering error propagation. J Comput Inf Syst 4(61172083):1593–1601

    Google Scholar 

  33. Ciardo G, Muppala J, Trivedi KS (1989) SPNP: stochastic Petri net package. In: Proceedings of the Third International Workshop, pp 142–151. https://doi.org/10.1109/PNPM.1989.68548

  34. Trivedi KS (2016) Probability and statistics with reliability, queuing and computer science applications. Wiley, Hoboken, p 830. https://doi.org/10.1002/9781119285441 ISBN: 9781119285427

    Book  MATH  Google Scholar 

  35. Bolch G, Greiner S, de Meer H, Trivedi KS (2006) Queueing networks and Markov chains. Wiley, Hoboken. https://doi.org/10.1002/0471791571 ISBN: 9780471791577

    Book  MATH  Google Scholar 

  36. Trivedi KS, Bobbio A (2017) Reliability and availability engineering: modeling, analysis, and applications, 1st edn. Cambridge University Press, Cambridge, p 730. https://doi.org/10.1017/9781316163047 ISBN: 9781316163047

    Book  Google Scholar 

  37. Al-Fares M, Loukissas A, Vahdat A (2008) A scalable commodity data center network architecture. https://doi.org/10.1145/1402946.1402967

  38. Alshahrani R, Peyravi H (2014) Modeling and simulation of data center networks. In: Proceedings of the 2nd ACM SIGSIM/PADS. ACM Press, New York, pp 75–82. https://doi.org/10.1145/2601381.2601389.18 ISBN: 9781450327947

  39. Guo C, Wu H, Tan K, Shi L, Zhang Y, Lu S (2008) Dcell. In: Proceedings of the ACM SIGCOMM 2008 Conference on Data Communication, vol 38. ACM Press, New York, p 75. https://doi.org/10.1145/1402958.1402968 ISBN: 9781605581750

  40. Li D, Guo C, Wu H, Tan K, Zhang Y, Lu S, Wu J (2011) Scalable and cost-effective interconnection of data-center servers using dual server ports. IEEE/ACM Trans Netw 19(1):102–114. https://doi.org/10.1109/TNET.2010.2053718

    Article  Google Scholar 

  41. Wang T, Su Z, Xia Y, Qin B, Hamdi M (2016) Towards cost-effective and low latency data center network architecture. Comput Commun 82:1–12. https://doi.org/10.1016/j.comcom.2016.02.016

    Article  Google Scholar 

  42. Lin D, Liu Y, Hamdi M, Muppala J (2012) Hyper-BCube: a scalable data center network. In: 2012 IEEE International Conference IEEE, pp 2918–2923. https://doi.org/10.1109/ICC.2012.6363759 ISBN: 978-1-4577-2053-6

  43. Wang T, Su Z, Xia Y, Liu Y, Muppala J, Hamdi M (2014) SprintNet: a high performance server-centric network architecture for data centers. In: 2014 IEEE International Conference on Communications (ICC), pp 4016–4021. https://doi.org/10.1109/ICC.2014.6883947

  44. Cao Y, Sun H, Trivedi KS, Han JJ (2002) System availability with non-exponentially distributed outages. IEEE Trans Reliab 51(2):193–198. https://doi.org/10.1109/TR.2002.1011525

    Article  Google Scholar 

  45. Distefano S, Trivedi KS (2013) Non-markovian state-space models in dependability evaluation. Qual Reliab Eng 29(2):225–239. https://doi.org/10.1002/qre.1305

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the 2018 KU Brain Pool Program of Konkuk University, South Korea. This work was partly supported by Institute for Information and Communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00121 Development of a Traffic Predictive Simulation SW for Improving the Urban Traffic Congestion). This research was partly supported by the Vietnam–Korea cooperation project: VAST.HTQT.HANQUOC.01/17-18 managed by the Vietnam Academy of Science and Technology (VAST), Vietnam. This research has also been financially supported in part by Grant PTNTD17.07 managed by the Vietnam Academy of Science and Technology (VAST), Vietnam.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Tuan Anh Nguyen or Dugki Min.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nguyen, T.A., Han, K., Min, D. et al. A stochastic reward net-based assessment of reliability, availability and operational cost for a software-defined network infrastructure. J Supercomput 75, 4657–4683 (2019). https://doi.org/10.1007/s11227-018-2677-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-018-2677-y

Keywords

Navigation