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Fuzzy Logic Load-Balancing Strategy Based on Software-Defined Networking

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Abstract

Traditional load balancing hardware is expensive and lacks scalability and flexibility. We propose a load balancing strategy based on fuzzy logic (LBSFL), which exploits the control and forwarding separation architecture characteristics of software-defined networking (SDN). First, the fuzzy membership function that affects the performance parameters of the server load is analyzed. Based on this, the load state of the virtual server is evaluated through fuzzy logic. Then the centralized control capability of SDN’s controllers for the whole network is utilized to monitor virtual server information in real time and to schedule virtual server tasks. Individual servers can be hibernated or restarted, to save power or to increase performance as necessary. Finally, the dynamic balance between the overall load, performance and energy consumption is realized. Simulation experiments showed that the proposed strategy improves overall performance of the network, especially when dealing with communication-intensive tasks and using a high-latency network.

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References

  1. McKeown, N.: Software-defined networking. INFOCOM Keynote Talk 17(2), 30–32 (2009)

    Google Scholar 

  2. McKeown, N., Anderson, T., Balakrishnan, H., et al.: OpenFlow: enabling innovation in campus networks. ACM SIGCOMM Comput. Commun. Rev. 38(2), 69–74 (2008)

    Article  Google Scholar 

  3. Namal, S., Ahmad, I., Gurtov, A., et al.: SDN based inter-technology load balancing leveraged by flow admission control. In: 2013 IEEE SDN for Future Networks and Services (SDN4FNS), pp. 1–5. IEEE (2013)

    Google Scholar 

  4. Marconett, D., Liu, L., Yoo, S.J.B.: Optical FlowBroker: load-balancing in software-defined multi-domain optical networks. In: Optical Fiber Communication Conference. Optical Society of America (2014): W2A. 44

    Google Scholar 

  5. Muñoz, P., Barco, R., de la Bandera, I.: Load balancing and handover joint optimization in LTE networks using fuzzy logic and reinforcement learning. Comput. Netw. 76, 112–125 (2015)

    Article  Google Scholar 

  6. Zhong, H., Fang, Y., Cui, J.: LBBSRT: an efficient SDN load balancing scheme based on server response time. Future Gener. Comput. Syst. 68, 183–190 (2017)

    Article  Google Scholar 

  7. Gandhi, R., Liu, H.H., Hu, Y.C., et al.: Duet: cloud scale load balancing with hardware and software. ACM SIGCOMM Comput. Commun. Rev. 44(4), 27–38 (2015)

    Article  Google Scholar 

  8. Wang, Y., Zhang, Y., Chen, J.: SDNPS: a load-balanced topic-based publish/subscribe system in software-defined networking. Appl. Sci. 6(4), 91 (2016)

    Article  Google Scholar 

  9. Handigol, N., Seetharaman, S., Flajslik, M., et al.: Plug-n-serve: load-balancing web traffic using OpenFlow. ACM Sigcomm Demo 4(5), 6 (2009)

    Google Scholar 

  10. Kaur, S., Singh, J., Kumar, K., et al.: Round-robin based load balancing in software defined networking. In: 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 2136–2139. IEEE (2015)

    Google Scholar 

  11. Zhang, H., Guo, X.: SDN-based load balancing strategy for server cluster. In: 2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems (CCIS), pp. 662–667. IEEE (2014)

    Google Scholar 

  12. Shang, Z., Chen, W., Ma, Q., et al.: Design and implementation of server cluster dynamic load balancing based on OpenFlow. In: 2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing (iCAST-UMEDIA), pp. 691–697. IEEE (2013)

    Google Scholar 

  13. Pakzad, F., Portmann, M., Tan, W.L., et al.: Efficient topology discovery in OpenFlow based software defined networks. Comput. Commun. 77, 52–61 (2016)

    Article  Google Scholar 

  14. Scott-Hayward, S.: Design and deployment of secure, robust, and resilient SDN controllers. In: 2015 1st IEEE Conference on Network Softwarization (NetSoft), pp. 1–5. IEEE (2015)

    Google Scholar 

  15. Hoang, D.B., Pham, M.: On software-defined networking and the design of SDN controllers. In: 2015 6th International Conference on the Network of the Future (NOF), pp. 1–3. IEEE (2015)

    Google Scholar 

  16. Kang, S.B., Kwon, G.I.: Load balancing strategy of SDN controller based on genetic algorithm. Mech. Eng. 129, 219–222 (2016)

    Google Scholar 

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Acknowledgments

The author would thank the support from projects of the national “863Program” (NO. 2015BAF09B02-3); the natural science fund of Tianjin city (NO. 17JCQNJC00500); Tianjin education science planning project of 13th five-year plan (HE3045); the fundamental research fund for the university in Tianjin, Tianjin Chengjian university (2016CJ12) and the fund of Tianjin Education Committee (20110813).

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Correspondence to Guoyan Li .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, G., Gao, T., Zhang, Z., Chen, Y. (2018). Fuzzy Logic Load-Balancing Strategy Based on Software-Defined Networking. In: Li, C., Mao, S. (eds) Wireless Internet. WiCON 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-319-90802-1_42

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  • DOI: https://doi.org/10.1007/978-3-319-90802-1_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90801-4

  • Online ISBN: 978-3-319-90802-1

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