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Fast recovery for online service function chaining interruption using adaptive migration

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Abstract

With the rapid development of wireless communication technology and the rapid popularization of various mobile devices, an increasing number of users want the ability to access their service requests conveniently anytime and anywhere. In order to avoid ongoing service interruption, the user’s SFC should be quickly migrated to ensure the continuation of mobile communication and seamless connection of online services (i.e., no interruption of ongoing services) when the user moves out of the service area of the original access point. However, most of the current research on service function chaining (SFC) migration focuses on how to achieve migration and ignores the fact that a rapid recovery response to avoid the sudden interruption of online services is the fundamental purpose of migration in this situation. This paper shows that implementing fast remapping on the mobile SFC is an assurance of its service continuity. And we propose a migration-aware and quick reresponse algorithm to realize the rapid migration and reresponse of mobile service requests. Furthermore, to ensure both the success rate and rationality of service migration, the algorithm also considers the operation cost and resource consumption of migration. The simulation results show that the algorithm effectively optimizes the migration time, and meanwhile it can choose the migration scheme with the highest matching degree for SFC based on the current network state efficiently and flexibly.

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References

  1. Bera, S., Misra, S., Vasilakos, A.: Software-defined networking for internet of things: a survey. IEEE Internet Things J. 4(6), 1994–2008 (2017)

    Article  Google Scholar 

  2. Chatras, B., Ozog, F.F.: Network functions virtualization: the portability challenge. IEEE Netw. 30(4), 4–8 (2016)

    Article  Google Scholar 

  3. Cui, L., Tso, F., Guo, S., et al.: Enabling heterogeneous network function chaining. IEEE Trans. Parallel Distrib. Syst. 30(4), 842–854 (2019)

    Article  Google Scholar 

  4. Mijumbi, R., Serrat, J., Gorricho, J., et al.: Network function virtualization: state-of-the-art and research challenges. IEEE Commun. Surv. Tutor. 18(1), 236–262 (2016)

    Article  Google Scholar 

  5. Sun, G., Chen, Z., Yu, H., et al.: Online parallelized service function chain orchestration in data center networks. IEEE Access 7(1), 100147–100161 (2019)

    Article  Google Scholar 

  6. Duan, Q., Ansari, N., Toy, M.: Software-defined network virtualization: an architectural framework for integrating SDN and NFV for service provisioning in future networks. IEEE Network 30(5), 10–16 (2016)

    Article  Google Scholar 

  7. Kaur, K., Garg, S., Kaddoum, G., et al.: An energy-driven network function virtualization for multi-domain software defined networks, pp. 121–126. The First International Workshop on Intelligent Cloud Computing and Networking, Paris (2019)

    Google Scholar 

  8. Xu, Z., Liang, W., Huang, M., et al.: Efficient NFV-Enabled Multicasting in SDNs. IEEE Trans. Commun. 67(3), 2052–2070 (2019)

    Article  Google Scholar 

  9. Garg, S., Kaur, K., Ahmed, S., et al.: MobQoS: mobility-aware and QoS-driven SDN framework for autonomous vehicles. IEEE Wirel. Commun. 26(4), 12–20 (2019)

    Article  Google Scholar 

  10. Sun, G., Zhou, R., Sun, J., et al.: Energy-efficient provisioning for service function chains to support delay-sensitive applications in network function virtualization. IEEE Internet Things J. 7(7), 6116–6131 (2020)

    Article  Google Scholar 

  11. Jia, Y., Wu, C., Li, Z., et al.: Online scaling of NFV service chains across geo-distributed datacenters. IEEE/ACM Trans. Networking 26(2), 699–710 (2018)

    Article  Google Scholar 

  12. Wang, C., Yuan, X., Cui, Y., et al.: Toward secure outsourced middlebox services: practices, challenges, and beyond. IEEE Network 32(1), 166–171 (2018)

    Article  Google Scholar 

  13. Linguaglossa, L., Lange, S., Pontarelli, S., et al.: Survey of performance acceleration techniques for network function virtualization. Proc. IEEE 107(4), 746–764 (2019)

    Article  Google Scholar 

  14. Rehman, A., Aguiar, R., Barraca, J.: Network functions virtualization: the long road to commercial deployments. IEEE Access 7, 60439–60464 (2019)

    Article  Google Scholar 

  15. Yan, Z., Zhang, P., Vasilakos, A.: A security and trust framework for virtualized networks and software defined networking. Secur. Commun. Netw. 9(16), 3059–3069 (2016)

    Article  Google Scholar 

  16. Medhat, A.M., Taleb, T., Elmangoush, A., et al.: Service function chaining in next generation networks: state of the art and research challenges. IEEE Commun. Mag. 55(2), 216–223 (2017)

    Article  Google Scholar 

  17. Sun, G., Zhu, G., Liao, D., et al.: Cost-efficient service function chain orchestration for low-latency applications in NFV networks. IEEE Syst. J. 13(4), 3877–3888 (2019)

    Article  Google Scholar 

  18. Xia, J., Cai, Z.P., Xu, M.: Optimized virtual network functions migration for NFV. IEEE 22nd International Conference on Parallel and Distributed Systems, Wuhan, 340–346 (2016)

  19. Eramo, V., Ammar, M., Lavacca, F.G.: Migration energy aware reconfigurations of virtual network function instances in NFV architectures. IEEE Access 5, 4927–4938 (2017)

    Article  Google Scholar 

  20. Carpio, F., Jukan, A., Pries, R.: Balancing the migration of virtual network functions with replications in data centers. IEEE/IFIP Network Operations and Management Symposium, Taibei, 1–8 (2018)

  21. Eramo, V., Miucci, E., Ammar, M., et al.: An approach for service function chain routing and virtual function network instance migration in network function virtualization architectures. IEEE/ACM Trans. Netw. 25(4), 2008–2025 (2017)

    Article  Google Scholar 

  22. Liu, J., Lu, W., Zhou, F., et al.: On dynamic service function chain deployment and readjustment. IEEE Trans. Netw. Serv. Manage. 14(3), 543–553 (2017)

    Article  Google Scholar 

  23. Sun, G., Xu, Z., Yu, H., et al.: Low-latency and resource-efficient service function chaining orchestration in network function virtualization. IEEE Internet Things J. 7(7), 5760–5772 (2020)

    Article  Google Scholar 

  24. Khoshnevisan, M., Joseph, V., Gupta, P., et al.: 5G industrial networks with CoMP for URLLC and time sensitive network architecture. IEEE J. Sel. Areas Commun. 37, 947–959 (2019)

    Article  Google Scholar 

  25. García-Morales, J., Lucas-Estañ, M.C., Gozalvez, J.: Latency-sensitive 5G RAN Slicing for Industry 4.0. IEEE Access 7, 143139–143159 (2019)

    Article  Google Scholar 

  26. Pointurier, Y., Benzaoui, N., Lautenschlaeger, W., et al.: End-to-end time-sensitive optical networking: challenges and solutions. J. Lightwave Technol. 37, 1732–1741 (2019)

    Article  Google Scholar 

  27. Garg, S., Kaur, K., Kaddoum, G., et al.: SDN based secure and privacy-preserving scheme for vehicular networks: a 5G perspective. IEEE Trans. Veh. Technol. 68(9), 8421–8434 (2019)

    Article  Google Scholar 

  28. Omer, D., Aburukba, R., Landolsi, T.: Optimization model for time sensitive IoT requests. International Conference on Communications, Signal Processing, and their Applications, Sharjah, 1–4 (2019)

  29. Farris, I., Orsino, A., Militano, L., et al.: Federations of connected things for delay-sensitive IoT services in 5G environments. IEEE International Conference on Communications, Paris, 1–6 (2017)

  30. Mohseni, H., Eslamnour, B.: Handover management for delay-sensitive IoT services on wireless software-defined network platforms. The 3rd International Conference on Internet of Things and Applications, San Diego, 1–6 (2019)

  31. Zhang, Q., Liu, F., Zeng, C.: Online Adaptive interference-aware VNF deployment and migration for 5G network slice. IEEE/ACM Transactions on Networking, early access: 1–14 (2021)

  32. Calvert, K K.L., Zegura, E.: Gt-itm: Georgia tech internetwork topology models (Software). Georgia Tech. http://www.cc.gatech.edu/fac/Ellen.Zegura/gt-itm/gt-itm.tar.gz

  33. Sun, J., Zhu, G., Sun, G., et al.: A reliability-aware approach for resource efficient virtual network function deployment. IEEE Access 6, 18238–18250 (2018)

    Article  Google Scholar 

Download references

Funding

This research was partially supported by the National Key Research and Development Program of China (2019YFB1802800).

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Authors and Affiliations

  1. Key Laboratory of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China

    Jingzhao Xie, Run Zhou, Gang Sun, Jian Sun & Hongfang Yu

  2. Agile and Intelligent Computing Key Laboratory of Sichuan Province, Chengdu, China

    Gang Sun

  3. Peng Cheng Laboratory, Shenzhen, China

    Hongfang Yu

Authors
  1. Jingzhao Xie
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  2. Run Zhou
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  3. Gang Sun
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  4. Jian Sun
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  5. Hongfang Yu
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Correspondence to Gang Sun.

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Xie, J., Zhou, R., Sun, G. et al. Fast recovery for online service function chaining interruption using adaptive migration. Cluster Comput 25, 1321–1339 (2022). https://doi.org/10.1007/s10586-021-03486-y

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  • DOI: https://doi.org/10.1007/s10586-021-03486-y

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