Wireless Personal Communications

, Volume 97, Issue 3, pp 3465–3482 | Cite as

Equal Size Clusters to Reduce Congestion in Wireless Multimedia Sensor Networks

  • Chaima BejaouiEmail author
  • Alexandre Guitton
  • Abdennaceur Kachouri


Wireless Multimedia Sensor Networks (WMSNs) are a particular instance of Wireless Sensor Networks that support the transmission of multimedia data such as video, image or sound. Those multimedia data should be delivered with a variety of predefined levels of Quality of Service swhich imposes the development of specific routing protocols. In this paper, we propose a new routing protocol based on clustering, that balances the number of nodes in clusters, called Equal Size Clusters to reduce Congestion in WMSNs. We seek to balance the number of members in each cluster in order to reduce intra-cluster congestion and reduce the number of congested cluster-heads. Therefore, we propose a novel metric called Maximum Cluster-heads Utilization Ratio (MCUR) that indicates the largest number of members assigned to a cluster-head to ensure a reliable transmission of multimedia data. Simulation results indicate that our proposed scheme outperforms other protocols proposed in the literature in terms of MCUR, number of cluster-heads and energy consumed.


WMSN WSN Clustering protocol Load-balancing MCUR 


  1. 1.
    Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.CrossRefGoogle Scholar
  2. 2.
    Zara, H., & Faisal, H. B. (2014). QoS in wireless multimedia sensor networks: A layered and cross-layered approach. Wireless Personal Communications, 75(1), 729–757.CrossRefGoogle Scholar
  3. 3.
    Chih-Yung, C., Kuei-Ping, S., & Shih-Chieh, L. (2005). ZBP: A zone-based broadcasting protocol for wireless sensor networks. Wireless Personal Communications, 33(1), 53–68.CrossRefGoogle Scholar
  4. 4.
    Akyildiz, I. F., Melodia, T., & Chowdury, K. R. (2007). Wireless multimedia sensor networks: A survey. IEEE Wireless Communications, 14(6), 1284–1536.CrossRefGoogle Scholar
  5. 5.
    Akyildiz, I. F., Melodia, T., & Chowdhury, K. R. (2007). A survey on wireless multimedia sensor networks. Computer Networks, 51(4), 921–960.CrossRefGoogle Scholar
  6. 6.
    Mohammed, A., Norshiela, F., Suleiman, Z., & Adel, A. (2013). Routing protocols for wireless multimedia sensor network: A survey. Journal of Sensors, 2013, 11.Google Scholar
  7. 7.
    Akkaya, K., & Younis, M. (2003). An energy-aware QoS routing protocol for wireless sensor network. In Proceedings workshops in the 23rd international conference on distributed computing systems (pp. 710–715).Google Scholar
  8. 8.
    Sun, Y., Ma, H., Liu, L., & Zhang, Y. (2008). ASAR: An ant-based service-aware routing algorithm for multimedia sensor networks. Frontiers of Electrical and Electronic Engineering in China, 3(1), 25–33.CrossRefGoogle Scholar
  9. 9.
    Cobo, L., Quintero, A., & Pierre, S. (2010). Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics. Computer Networks, 54(17), 2991–3010.CrossRefGoogle Scholar
  10. 10.
    Tian, H., Stankovic, J. A., Chenyang, L., & Abdelzaher, T. (2003). SPEED: A stateless protocol for real-time communication in sensor networks. In proceedings of 23rd international conference on distributed computing systems, Providence (pp. 46–55).Google Scholar
  11. 11.
    Denis, R., Rodrigo, C., Helder, P., Kssio, M., Eduardo, C., Torsten, B., et al. (2012). A hierarchical multi-hop multimedia routing protocol for wireless multimedia sensor networks. Network Protocols and Algorithms, 4(4), 44–64.Google Scholar
  12. 12.
    Zhi-yuan, L., & Ru-chuan, W. (2010). Load balancing-based hierarchical routing algorithm for wireless multimedia sensor networks. Journal of China Universities of Posts and Telecommunications, 17, 51–59.Google Scholar
  13. 13.
    Guannan, S., Jiandong, Q., Zhe, Z., & Qiuhong, Q. (2011). A reliable multipath routing algorithm with related congestion control scheme in wireless multimedia sensor networks. In Proceedings of the 3rd international conference on computer research and development (pp. 229–233).Google Scholar
  14. 14.
    Mande, X., & Yuanyan, G. (2010). Multipath routing algorithm for wireless multimedia sensor networks within expected network lifetime. In Proceedings of the international conference on communications and mobile computing (pp. 284–287).Google Scholar
  15. 15.
    Wendi, H. (2000). Energy-efficient communication protocol for wireless sensor networks. Ph.D. thesis, Cornell University.Google Scholar
  16. 16.
    Yong, Y., & Hongbo, C. (2012). An congestion avoidance and alleviation routing protocol in sensor networks. Advances in Electric and Electronics, LNEE (vol. 155, pp. 99–106). Springer.Google Scholar
  17. 17.
    Jeya, S. S., & Paramasivan, B. (2015). CRAP: Cluster based congestion control with rate adjustment based on priority in wireless sensor networks. International Journal of Multimedia and Ubiquitous Engineering, 10(2), 421–436.CrossRefGoogle Scholar
  18. 18.
    Yanlin, L., & Mark, C. (2000). Using redundancy to repair video damaged by network data loss. In Proceedings of ACM/SPIE multimedia computing and networking (MMCN).Google Scholar
  19. 19.
    Tejal, I., & Prachi, J. (2013). Cluster and traffic distribution protocol for energy consumption in wireless sensor network. In Engineering and systems.Google Scholar
  20. 20.
    Zhiping, Z., & Ting, W. (2012). An energy balanced cluster algorithm for wireless sensor networks. In Proceedings of the 24th Chinese control and decision conference IEEE.Google Scholar
  21. 21.
    Kui, X.-Y., Wang, J.-X., & Zhang, S.-G. (2012). Energy-balanced clustering protocol for data gathering in wireless sensor networks with unbalanced traffic load. Journal Central South University, 19(11), 3180–3187.CrossRefGoogle Scholar
  22. 22.
    Quynh, T. N., Phung, K. H., & Quoc, H. V. (2012). Improvement of energy consumption and load balance for LEACH in wireless sensors networks. In ICTC IEEE.Google Scholar
  23. 23.
    Wangang, W., & Yong, P. (2013). LEACH algorithm based on load balancing. TELKOMNIKA, 11(9), 5329–5335.Google Scholar
  24. 24.
    Heewook, S., Sangman, M., Ilyong, C., & Moonsoo, K. (2014). Equal-size clustering for irregularly deployed wireless sensor networks. Journal of Wireless Personal Communications, 82(2), 995–1012.Google Scholar
  25. 25.
    Mucheol, K., Sunhong, K., Hyungjin, B., & Sangyong, H. (2009). Optimized algorithm for balancing clusters in wireless sensor networks. Journal of Zhejiang University Science A, 10(10), 1404–1412.CrossRefGoogle Scholar
  26. 26.
    Mian, J. A., Priyadarsi, N., Xiangjian, H., & Ren, L. P. (2014). PASCCC: Priority-based application-specific congestion control clustering protocol. Computer Networks, 74, 92–102.CrossRefGoogle Scholar
  27. 27.
    Vipin, P., Girdhari, S., & Yadav, R. P. (2015). Balanced cluster size solution to extend lifetime of wireless sensor networks. IEEE Internet of Things Journal, 2(5), 2327–4662.Google Scholar
  28. 28.
    Bejaoui, C., Guitton, A., & Kachouri, A. (2015). Improved election of cluster-heads in LEACH. In Proceedings of IEEE/ACS international conference on computer systems and applications, Morroco.Google Scholar
  29. 29.
    Network simulator.

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Chaima Bejaoui
    • 1
    Email author
  • Alexandre Guitton
    • 2
  • Abdennaceur Kachouri
    • 1
  1. 1.LETI Research Lab, National School of Engineers of SFAXUniversity of SFAXSFAXTunisia
  2. 2.CNRS, LIMOSUniversity of Clermont AuvergneClermont-FerrandFrance

Personalised recommendations