Telecommunication Systems

, Volume 38, Issue 3–4, pp 121–132 | Cite as

Coverage based inter cluster communication for load balancing in heterogeneous wireless sensor networks

  • N. IsrarEmail author
  • I. Awan


Effective energy management in heterogeneous wireless sensor networks is more challenging issue compared to homogeneous wireless sensor networks. Much of the existing research focuses on homogeneous wireless sensor networks. The energy conservation schemes for the homogeneous wireless sensor networks do not perform efficiently when applied to heterogeneous wireless sensor networks. The proposed algorithm in this paper exploits the redundancy properties of the wireless sensor networks and also changes the inter cluster communication pattern depending on the energy condition of the high energy nodes during the life cycle of the heterogeneous wireless sensor networks. Performance studies indicate that the proposed algorithm effectively solves the problem of load balancing across the network and is more energy efficient compared to multi hop versions of the standard low energy adaptive clustering hierarchy protocol.


Distributed clustering Efficient cluster based routing Energy efficient routing Multilayer clustering 


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  1. 1.
    Baptista, A., Steere, D. C., McNamee, D., Pu, C., & Walpole, J. (2000). Research challenges in environmental observation and forecasting systems. In Proceedings of the 6th annual international conference on Mobile computing and networking (pp. 292–299). Google Scholar
  2. 2.
    Biagionni, E., & Bridges, K. (2002). The application of remote sensor technology to assist the recovery of rare and endangered species. Special issue on Distributed Sensor Networks for the International Journal of High Performance Computing Applications (pp. 112–121). Google Scholar
  3. 3.
    Biagionni, E., & Sasaki, G. (2003). Wireless sensor placement for reliable and effficient data collection. In Proceedings of the Hawaiii international conference on systems sciences (p. 127). Google Scholar
  4. 4.
    Chandrakasan, A., Heinzelman, W. R., & Balakrishnan, H. (2000). Energy-efficient communication protocols for wireless microsensor networks. Hawaii International Conference on System Sciences (pp. 1–10). Google Scholar
  5. 5.
    Estrin, D., Wang, H., & Girod, L. (2003). Preprocessing in a tiered sensor network for habitat monitoring. EURASIP JASP special issue of sensor networks (pp. 392–401). Google Scholar
  6. 6.
    Gao, J., Sohrabi, K., Ailawadhi, V., & Pottie, G. (2000). Protocols for self-organization of a wireless sensor network. IEEE Personal Communications Magazine (pp. 16–27). Google Scholar
  7. 7.
    Govindan, R., & Intanagonwiwat, D. E. C. (2000). Directed diffusion: a scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th annual ACM/IEEE international conference on mobile computing and networking (pp. 56–67). Google Scholar
  8. 8.
    Gupta, G., & Younis, M. (2003). Load-balanced clustering of wireless sensor networks. IEEE International Conference on Communications (pp. 1848–1852). Google Scholar
  9. 9.
    Han, C. C., Savvides, A., & Srivastava, M. (2001). Dynamic fine-grained localization in ad-hoc networks of sensors. In The Proceedings of the 7th annual international conference on Mobile computing and networking (pp. 166–179). Google Scholar
  10. 10.
    Heidemann, J., Bulusu, N., & Estrin, D. (2000). GPS-less low cost out door localization for very small devices. http//
  11. 11.
    Heinzelman, W. (2002). Application specific protocol architecture for wireless sensor network. IEEE Transactions on Wireless Communications. Google Scholar
  12. 12.
    Lin, F., & Du, X. (2005). Desingning efficient routing protocols for heterogeneous sensor networks. 24th IEEE confrence on performance, computing, and communications (pp. 51–58). Google Scholar
  13. 13.
    Matta, I., Bestavros, A., & Smaragdakis, G. (2004). SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. Second International Workshop on Sensor and Actor Network Protocols and Applications. Google Scholar
  14. 14.
    Rosenberg, C., & Mhatre, V. (2004). Homogeneous vs heterogeneous clustered sensor networks: a comparative study. IEEE International Conference on Communications (pp. 3645–3651). Google Scholar
  15. 15.
    Rosenberg, C., & Mhatre, V. P. (2005). A minimum cost heterogeneous sensor network with a lifetime constraint. IEEE Transactions on Mobile Computing (pp. 4–16). Google Scholar
  16. 16.
    Tian, D., & Georganas, N. D. (2003). A node scheduling scheme for energy conservation in large wireless sensor networks. Wireless Communication and Mobile Computing by Wiley (pp. 271–290). Google Scholar
  17. 17.
    Wang, X., Akyildiz, I. F., & Wang, W. (2002). Wireless sensor networks: a survey. Computer Networks (pp. 393–422). Google Scholar
  18. 18.
    Younis, O., & Fahmy, S. (2004). HEED: a hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks. IEEE Transactions on Mobile Computing (pp. 366–379). Google Scholar
  19. 19.
    Zhu, Q., Wang, M., & Qing, L. (2006). Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer Communications by Elsevier (pp. 2230–2237). Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.School of InformaticsUniversity of BradfordBradfordUK

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