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Network Availability Evaluation Based on Markov Chain of QoS-Aware

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Abstract

In complex networks, availability evaluation performs unsatisfactorily because the quality of service (QoS) is constrained by performance cost. This causes conventional evaluation only focuses on the failure probability of network devices as to indiscriminately maintain service at the same expense, leading to the performance cost increasing and available resource wasting. We developed a conceptually different evaluation approach, a Markov Chain with QoS based Network Availability (MCQNA), to identify the minimum performance cost of various businesses according to QoS metrics. Based on the analysis of limit probability of MCQNA, the values of the steady distribution were computed as the dynamic weight coefficients in performance cost. This paper details the MCQNA design and evaluates its performance in normal and heavy workloads. The evaluation results indicate that MCQNA with QoS indices judging performance cost is more reasonable and sensitive than the typical scheme. The study provided guidance for implementing strategy in networks.

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References

  1. Li, J., Yang, L., Fu, X., Chao, F., & Qu, Y. (2017) Dynamic QoS solution for enterprise networks using TSK fuzzy interpolation. In: 2017 IEEE international conference on fuzzy systems (FUZZ-IEEE), pp. 1–6.

  2. Ma, H., Zhu, H., Hu, Z., Tang, W., & Dong, P. (2017). Multi-valued collaborative QoS prediction for cloud service via time series analysis. Future Generation Computing Systems,68, 275–288.

    Article  Google Scholar 

  3. Morris, K., Kim, D. S., Wood, A., & Woodward, G. (2017) Availability and resiliency analysis of modern distribution grids using stochastic reward nets. In: 2017 IEEE innovative smart grid technologies: Asia (ISGT-Asia), pp. 1–5.

  4. Jirong, Z., & Yongbao, L. (2017). Resource allocation algorithm for relay systems based on QoS guarantees. Application Research of Computers,34(12), 3788–3791.

    Google Scholar 

  5. Souza, R., Santos, M., & Fernandes, S. (2018) Importance measures for NFV data center: An availability evaluation. 5th An. do Work. Pre-IETF (WPIETF 2018).

  6. Phung-Duc, T. & Tuan (2014) Server farms with batch arrival and staggered setup. In: Proceedings of the fifth symposium on information and communication technology—SoICT ’14, 2014, pp. 240–247.

  7. She, C., Chen, Z., Yang, C., Quek, T. Q. S., Li, Y., & Vucetic, B. (2018). Improving network availability of ultra-reliable and low-latency communications with multi-connectivity. IEEE Transactions on Communications,66(11), 5482–5496.

    Article  Google Scholar 

  8. Du, S., Zio, E., & Kang, R. (2018). A new analytical approach for interval availability analysis of Markov repairable systems. IEEE Transactions on Reliability,67(1), 118–128.

    Article  Google Scholar 

  9. Kadamus, G., & Langer, M. (2018). Measurements and statistical analysis for assessment of availability of mobile network services. Journal of Telecommunications and Information Technology,2, 48–52.

    Article  Google Scholar 

  10. Shan, X., Wang, P., & Lu, W. (2017). The reliability and availability evaluation of repairable district heating networks under changeable external conditions. Applied Energy,203, 686–695.

    Article  Google Scholar 

  11. Wang, W., & Doucette, J. (2018). Optimized design and availability analysis of large-scale shared backup path protected networks. Telecommun. Syst.,68(2), 351–372.

    Article  Google Scholar 

  12. Xiuting, S., Jun, N., Qingbo, G., & Zhen, L. (2017). Web services selection strategy based on combination weighting approach. Appl. Res. Comput.,34(8), 8–12.

    Google Scholar 

  13. Yanli, L., & Yixin, Y. (2017). An effective method to formulate state transition probability matrix of Markov model of large-scale system. Journal of Tianjin University of Technology,46(9), 791–798.

    Google Scholar 

  14. Wang, T. H., Chen, Y. C., Huang, S. K., Hsu, C. M., Liao, B. H., & Young, H. C. (2015). An efficient scheme of bulk traffic statistics collection for software-defined networks. In: 17th Asia-Pacific network operations and management symposium: a very connect world, APNOMS 2015, pp. 360–363.

  15. Chang, B.-J., Liang, Y.-H., & Lee, Y.-H. (2013). Dynamic-cost-reward connection admission control for maximizing system reward in 4G wireless multihop relaying networks. Computer Networks,57(13), 2643–2655.

    Article  Google Scholar 

  16. Hayyolalam, V., & Pourhaji Kazem, A. A. (2018). A systematic literature review on QoS-aware service composition and selection in cloud environment. Journal of Network and Computer Application,110, 52–74.

    Article  Google Scholar 

  17. Kuperman, G., Sun, J., Cheng, B.-N., Deutsch, P., & Narula-Tam, A. (2018). Group centric networking: A new approach for wireless multi-hop networking. Ad Hoc Networks,79, 160–172.

    Article  Google Scholar 

  18. Wust, C. C., Steffens, L., & Bril, R. J. (2004). QoS control strategies for high-quality video processing. In: Proceedings 16th euromicro conference on real-time systems, 2004. ECRTS, pp. 3–12.

  19. Alashaikh, A., Gomes, T., & Tipper, D. (2015). The Spine concept for improving network availability. Computer Networks,82, 4–19.

    Article  Google Scholar 

  20. Usman, M. R., & Shin, S. Y. (2016). Channel allocation schemes for permanent user channel assignment in wireless cellular networks. IETE Journal of Research,62(2), 189–197.

    Article  Google Scholar 

  21. Matos, R., Romero, P., Maciel, M., Silva, R. M. A. & Maciel, P. R. M. (2016). IJWGS12104 Matos et al machine learning in vision view project improving mobile cloud performance using offloading techniques and stochastic models view project.

  22. Usman, M. R., Usman, M. A., & Shin, S. Y. (2017). Channel resource allocation and availability prediction in hybrid access femtocells. Physics Communication,24, 112–122.

    Article  Google Scholar 

  23. Li, W., Ma, X., Wu, J., Trivedi, K. S., Huang, X.-L., & Liu, Q. (2017). Analytical model and performance evaluation of long-term evolution for vehicle safety services. IEEE Transactions on Vehicular Technology,66(3), 1926–1939.

    Article  Google Scholar 

  24. Gandhi, A., Harchol-Balter, M., & Adan, I. (2010). Server farms with setup costs. Performance Evaluation,67(11), 1123–1138.

    Article  Google Scholar 

  25. Wang, J., Wang, L., Wang, C.-H., & Zhang, Z. (2017). Hierarchical Markov model used in the reliability assessment and management of low-voltage switchgear. Special Issue Artic Advance in Mechanical Engineering,9(9), 2017.

    Google Scholar 

  26. Hu, Z., & Luo, J. (2015). Cracking network monitoring in DCNs with SDN. Proceedings of IEEE INFOCOM,26, 199–207.

    Google Scholar 

  27. ns-3 Implementation of Fat-tree Architecture. https://github.com/ntu-dsi-dcn/ntu-dsi-dcn, 2015.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Xi’an Technological University, Xi’an, 710021, China

    Junyong Tang, Chenlu Ma & Penghui Tian

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  1. Junyong Tang
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  2. Chenlu Ma
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  3. Penghui Tian
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Correspondence to Junyong Tang.

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Tang, J., Ma, C. & Tian, P. Network Availability Evaluation Based on Markov Chain of QoS-Aware. Wireless Pers Commun 113, 1673–1689 (2020). https://doi.org/10.1007/s11277-020-07286-2

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