SDN Based Content-Centric QoS-Guaranteed for Wireless Multimedia Sensor Networks

  • Gaolei Li
  • Jun WuEmail author
  • Jianhua Li
  • Kuan Wang
  • Shan He
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 221)


As the deployment of wireless multimedia sensor networks (WMSNs) increases sharply, the control granularity of traditional quality of service (QoS) technologies present weak assistance to satisfy the various application requirements. In this paper, we propose a novel architecture of software-defined network (SDN) based content-centric QoS-guaranteed (SCQG) for WMSNs. The SDN is an innovative network paradigm, which has capability to uniformly monitor and control the WMSNs’ infrastructures automatically. In proposed architecture, we formulate proper priority for each content based on its popularity in WMSNs. And also, we extend the SDN controller to match the content and make flow tables each content requests. Besides, we design an k-nearest neighbor (KNN) based machine-learning algorithm to identify the popularity of different contents.


Wireless multimedia sensor networks (WMSNs) Software-defined network (SDN) Content-centric QoS-guaranteed Popularity k-nearest neighbor (KNN) 



This work was supported by the National Science Foundation of China (Grant No. 61401273 and 61431008) and Shanghai Science and Technology Committee (Grant No. 15PJ1433800 and 14DZ1104903).


  1. 1.
    Baccarelli, E., Chiti, F., Cordeschi, N., Fantacci, R., Marabissi, D., Parisi, R., Uncini, A.: Green multimedia wireless sensor networks: distributed intelligent data fusion, in-network processing, and optimized resource management. IEEE Wirel. Commun. 21(4), 20–26 (2014)CrossRefGoogle Scholar
  2. 2.
    Gaolei, L., Mianxiong, D., Kaoru, O., Jun, W., Jianhua, L., Tianpeng, Y.: Towards QoE named content-centric wireless multimedia sensor networks with mobile sinks. In: IEEE International Conference on Communication (ICC) (2017)Google Scholar
  3. 3.
    Kreutz, D., Ramos, F.M.V., Esteves Verissimo, P., Esteve Pothenberg, C., Azodolmolky, S., Uhlig, S.: Software-defined networking: a comprehensive survey. Proc. IEEE 103(1), 14–76 (2015)CrossRefGoogle Scholar
  4. 4.
    McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., Turner, J.: OpenFlow: enabling innovation in campus networks. ACM SIGCOMM Comput. Commun. Rev. 38(2), 69–74 (2008)CrossRefGoogle Scholar
  5. 5.
    Lara, A., Kolasani, A., Ramamurthy, B.: Network innovation using OpenFlow: a survey. IEEE Commun. Surv. Tutor. 16(1), 493–512 (2014)CrossRefGoogle Scholar
  6. 6.
    Akyildiz, I.F., Lee, A., Wang, P., et al.: A roadmap for traffic engineering in SDN-OpenFlow networks. Comput. Netw. 71(4), 1–30 (2014)Google Scholar
  7. 7.
    Agarwal, S., Kodialam, M., Lakshman, T.V.: Traffic engineering in software defined networks. In: INFOCOM, 2013 Proceedings IEEE, pp. 2211–2219. IEEE (2013)Google Scholar
  8. 8.
    Yassine, A., Rahimi, H., Shirmohammadi, S.: Software defined network traffic measurement: current trends and challenges. Instrum. Meas. Mag. IEEE 18(2), 42–50 (2015)CrossRefGoogle Scholar
  9. 9.
    Yong, C., Shihan, X., Chunpeng, L., Stojmenovic, I., Minming, L.: Data centers as software defined networks: traffic redundancy elimination with wireless cards at routers. IEEE J. Sel. Areas Commun. 31(12), 2658–2672 (2013)CrossRefGoogle Scholar
  10. 10.
    Qazi, Z.A., Lee, J., Jin, T., et al.: Application-awareness in SDN. ACM SIGCOMM Comput. Commun. Rev. 43(4), 487–488 (2013)CrossRefGoogle Scholar
  11. 11.
    Zhenyun, Z., Tae-Young, C., Raghupathy, S., Aravind, V.: Application-aware acceleration for wireless data networks: design elements and prototype implementation. IEEE Trans. Mob. Comput. 8(9), 1280–1295 (2009)CrossRefGoogle Scholar
  12. 12.
    Amemiya, K., Abiru, K., Ishihara, T.: Application-aware traffic control for network-based data processing services. In: IEEE International Conference on Intelligence in Next Generation Networks (ICIN), pp. 142–147 (2012)Google Scholar
  13. 13.
    Jarschel, M., Wamser, F., Hohn, T., Zinner, T., Tran-Gia, P.: SDN based application-aware networking on the example of YouTube video streaming. In: 2013 Second European Workshop on Software Defined Networks (EWSDN), vol. 87, no. 92 (2013)Google Scholar
  14. 14.
    Gaolei, L., Mianxiong, D., Kaoru, O., Jun, W., Jianhua, L., Tianpeng, Y.: Deep packet inspection based application-aware traffic control for software defined networks. In: IEEE Global Communication Conference, pp. 1–6 (2017)Google Scholar
  15. 15.
    Chang-Su, M., Sun-Hyung, K.: A study on the integrated security system based real-time network packet deep inspection. Int. J. Secur. Appl. 8(1), 113–122 (2014)Google Scholar
  16. 16.
    Al-Anbagi, I., Erol-Kantarci, M., Mouftah, H.T.: A survey on cross-layer quality-of-service approaches in WSNs for delay and reliability aware applications. IEEE Commun. Surv. Tutor. 18(1), 525–552 (2016)CrossRefGoogle Scholar
  17. 17.
    Kaulbars, D., Schweikowski, F., Wietfeld, C.: Spatially distributed traffic generation for stress testing the robustness of mission critical smart grid communication. In: IEEE Globecom Workshops (GC Wkshps) (2015)Google Scholar
  18. 18.
    Spachos, P., Toumpakaris, D., Hatzinakos, D.: QoS and energy-aware dynamic routing in wireless multimedia sensor networks. In: IEEE International Conference on Communications (ICC), pp. 6935–6940 (2015)Google Scholar
  19. 19.
    Kogan, K., Nikolenko, S., Culhane, W., et al.: Towards efficient implementation of packet classifiers in sdn/OpenFlo. In: Proceedings of the Second ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking, pp. 153–154 (2013)Google Scholar
  20. 20.
    Dainotti, A., Pescape, A., Claffy, K.C.: Issues and future directions in traffic classification. IEEE Netw. 26(1), 35–40 (2012)CrossRefGoogle Scholar
  21. 21.
    Finsterbusch, M., Richter, C., Rocha, E., Muller, J.-A., Hanssgen, K.: A survey of payload-based traffic classification approaches. IEEE Commun. Surv. Tutor. 16(2), 1135–1156 (2014)CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  • Gaolei Li
    • 1
  • Jun Wu
    • 1
    Email author
  • Jianhua Li
    • 1
  • Kuan Wang
    • 1
  • Shan He
    • 1
  1. 1.School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina

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