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Enhancing the Performance of Software-Defined Wireless Mesh Network

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International Conference on Communication, Computing and Electronics Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 637))

Abstract

In a software-defined wireless mesh network, a centralized manner of managing and monitoring of the network occurs. The software-defined network (SDN) is the future of the upcoming generation network paradigm by separating control plane and data plane such that network management and optimization can be conducted in a centralized manner using global network information. In this paper, we proposed a novel architecture of software-defined wireless mesh networks to identify the issues of traffic balancing introduced due to node mobility. In order to reduce the overall response time of the SDN controller in the dynamic network topology, the new model predicts the probability of the link failure in the topology. Once the link failure is predicted, alternate selection of various routes proposed through the effective stability of traffic in the network is achieved and thereby overhead of the control plane is minimized. Utilizing ns-3 to efficiently address the above problem, we can enhance the network throughput and packet delivery fraction and minimize the delay in the network. Finally, performance is evaluated via extensive simulations.

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References

  1. Peng, Y., Guo, L., Deng, Q., Ning, Z., Zhang, L.: A novel hybrid routing forwarding algorithm in SDN enabled wireless mesh networks. In: 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems, New York, NY, pp. 1806–1811 (2015).https://doi.org/10.1109/hpcc-css-icess.2015.271

  2. Detti, A., Pisa, C., Salsano, S., Blefari-Melazzi, N.: Wireless mesh software defined networks (wmSDN). In: 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Lyon, pp. 89–95 (2013).https://doi.org/10.1109/wimob.2013.6673345

  3. Abolhasan, M., Lipman, J., Ni, W., Hagelstein, B.: Software-defined wireless networking: centralized, distributed, or hybrid? Netw. IEEE 29, 32–38 (2015). J. Netw. Comput. Appl. 61 n.C, 199–221 (2016). doihttps://doi.org/10.1016/j.jnca.2015.11.012

    Article  Google Scholar 

  4. Yu, H.C., Quer, G., Rao, R.R.: Wireless SDN mobile ad hoc network: from theory to practice. In: 2017 IEEE International Conference on Communications (ICC), Paris, pp. 1–7 (2017). https://doi.org/10.1109/icc.2017.7996340

  5. Labraoui, M., Boc, M., Fladenmuller, A.: Self-configuration mechanisms for SDN deployment in wireless mesh networks. In: 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), Macau, pp. 1–4 (2017).doi: 10.1109/WoWMoM.2017.7974352

    Google Scholar 

  6. Magdalene, W., Let, G.S.: Implementation of dynamic generation size adjustment algorithm for cognitive radio ad-hoc network. In: 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, pp. 119–122 (2016). https://doi.org/10.1109/wispnet.2016.7566103

  7. Fathy, M., Tammam, A., Saafan, A.: Mitigating the impact of malicious behavior via utilizing multiple routes in a cooperative sensing cognitive radio network. In: 2017 IEEE 15th Student Conference on Research and Development (SCOReD), Putrajaya, pp. 247–252 (2017). https://doi.org/10.1109/scored.2017.8305384

  8. Laghate, M., Cabric, D.: Cooperatively learning footprints of multiple incumbent transmitters by using cognitive radio networks. IEEE Trans. Cogn. Commun. Netw. 3(3), 282–297 (2017). https://doi.org/10.1109/TCCN.2017.2710309

    Article  Google Scholar 

  9. AlShammari, T., Hamdaoui, B., Guizani, M., Rayes, A.: Overcoming user selfishness in DSA systems through credit-based resource allocation. In: 2014 IEEE International Conference on Communications (ICC), Sydney, NSW, pp. 318–323 (2014). https://doi.org/10.1109/icc.2014.6883338

  10. Choi, H., Lee, I., Lee, H.: Delay analysis of carrier sense multiple access with collision resolution. J. Commun. Netw. 17(3), 275–285 (2015). https://doi.org/10.1109/JCN.2015.000050

    Article  Google Scholar 

  11. Fu, C.P., Liew, S.C.: TCP Veno: TCP enhancement for transmission over wireless access networks. IEEE J. Sel. Areas Commun. 21(2), 216–228 (2003). https://doi.org/10.1109/jsac.2002.807336

    Article  Google Scholar 

  12. Keerthan Kumar, T.G., Virupakshaiah, H.K., Nanda K.V.: Ensuring an online chat mechanism with accountability to sharing the non-downloadable file from the cloud. In: 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), Bangalore, pp. 718–721 (2016). https://doi.org/10.1109/icatcct.2016.7912093

  13. Chen, Z., et al.: A novel bandwidth estimation algorithm of TCP westwood in typical LTE scenarios. In: 2015 IEEE/CIC International Conference on Communications in China (ICCC), Shenzhen, pp. 1–5 (2015).https://doi.org/10.1109/iccchina.2015.7448600

  14. Alrshah, M.A., Othman, M.: Performance evaluation of parallel TCP, and its impact on bandwidth utilization and fairness in high-BDP networks based on test-bed. In: 2013 IEEE 11th Malaysia International Conference on Communications (MICC), Kuala Lumpur, pp. 23–28 (2013). https://doi.org/10.1109/micc.2013.6805793

  15. Jiang, X., Jin, G.: CLTCP: an adaptive TCP congestion control algorithm based on congestion level. IEEE Commun. Lett. 19(8), 1307–1310 (2015). https://doi.org/10.1109/LCOMM.2015.2447541

    Article  Google Scholar 

  16. Wang, J., Wen, J., Zhang, J., Xiong, Z., Han, Y.: TCP-FIT: an improved TCP algorithm for heterogeneous networks. J. Netw. Comput. Appl. 71, pp. 167–180 (2016). ISSN 1084-8045. https://doi.org/10.1016/j.jnca.2016.03.020

    Article  Google Scholar 

  17. Le, T.A., Hong, C.S., Razzaque, M.A., Lee, S., Jung, H.: ecMTCP: an energy-aware congestion control algorithm for multipath TCP. IEEE Commun. Lett. 16(2), 275–277 (2012). https://doi.org/10.1109/LCOMM.2011.120211.111818

    Article  Google Scholar 

  18. Lee, H.-J., Lim, J.-T.: Congestion control for streaming service in IEEE 802.11 multihop networks. Commun. IET. 4, 1415–1422 (2010). https://doi.org/10.1049/iet-com.2009.0376

    Article  MathSciNet  MATH  Google Scholar 

  19. O’malley, S.W., Brakmo, L.S., Peterson, L.L.: TCP Vegas: New techniques for congestion detection and avoidance. ACM Comput. Commun. Rev. (CCR) 24 (1994). https://doi.org/10.1145/190809.190317

    Article  Google Scholar 

  20. Wei, D.X., Jin, C., Low, S.H., Hegde, S.: FAST TCP: motivation, architecture, algorithms, performance. IEEE/ACM Trans. Netw. 14(6), 1246–1259 (2006). https://doi.org/10.1109/TNET.2006.886335

    Article  Google Scholar 

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Shastry, N., Keerthan Kumar, T.G. (2020). Enhancing the Performance of Software-Defined Wireless Mesh Network. In: Bindhu, V., Chen, J., Tavares, J. (eds) International Conference on Communication, Computing and Electronics Systems. Lecture Notes in Electrical Engineering, vol 637. Springer, Singapore. https://doi.org/10.1007/978-981-15-2612-1_1

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  • DOI: https://doi.org/10.1007/978-981-15-2612-1_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2611-4

  • Online ISBN: 978-981-15-2612-1

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