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Clustering Versus Evenly Distributing Energy Dissipation in Wireless Sensor Routing for Prolonging Network Lifetime

  • Guangyan Huang
  • Xiaowei Li
  • Jing He
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3992)

Abstract

A novel Cluster Heads (CH) choosing algorithm based on both Minimal Spanning Tree and Maximum Energy resource on sensors, named MSTME, is provided for prolonging lifetime of wireless sensor networks. MSTME can satisfy three principles of optimal CHs: to have the most energy resource among sensors in local clusters, to group approximately the same number of closer sensors into clusters, and to distribute evenly in the networks in terms of location. Simulation shows the network lifetime in MSTME excels its counterparts in two-hop and multi-hop wireless sensor networks.

Keywords

Wireless Sensor Network Cluster Head Network Lifetime Minimal Span Tree Prolong Network Lifetime 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Chandrakasan, A., Amirtharajah, R., Cho, S.-H., Goodman, J., Konduri, G., Kulik, J., Rabiner, W., Wang, A.: Design Considerations for Distributed Microsensor Networks. In: Proc. IEEE Custom Integrated Circuits Conference, pp. 279–286 (1999)Google Scholar
  2. 2.
    Clare, L., Pottie, G., Agre, J.: Self-Organizing Distributed Sensor Networks. In: Proc. SPIE Conf. Unattended Ground Sensor Technologies and Applications, pp. 229–237 (1999)Google Scholar
  3. 3.
    Dong, M., Yung, K., Kaiser, W.: Low Power Signal Processing Architectures for Network Microsensors. In: Proc. Int’l Symp. Low Power Electronics and Design, pp. 173–177 (1997)Google Scholar
  4. 4.
    Estrin, D., Govindan, R., Heidemann, J., Kumar, S.: Next Century Challenges: Scalable Coordination in Sensor Networks. In: Proc. ACM/IEEE Mobicom (1999)Google Scholar
  5. 5.
    Kulik, J., Rabiner, W., Balakrishnan, H.: Adaptive Protocols for Information Dissemination in Wireless Sensor Networks. In: Proc. ACM/IEEE Mobicom (1999)Google Scholar
  6. 6.
    Xu, Y., Heidemann, J., Estrin, D.: Geography-Informed Energy Conservation for Ad Hoc Routing. In: Proc. SIGMOBILE (2001)Google Scholar
  7. 7.
    Al-Karaki, J.N., Kamal, A.E.: Routing Techniques in Wireless Sensor Networks: A Survey. IEEE Wireless Communications 11, 6–28 (2004)CrossRefGoogle Scholar
  8. 8.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A Survey on Sensor Networks. IEEE Communications Magazine 40, 102–114 (2002)CrossRefGoogle Scholar
  9. 9.
    Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: Energy Efficient Communication Protocol for Wireless Microsensor Networks. In: Proc. Hawaii Int’l. Conf. Sys. Sci. (2000)Google Scholar
  10. 10.
    Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An Application-Specific Protocol Architecture for Wireless Microsensor Networks. IEEE Transactions on Wireless Communications 1, 660–670 (2002)CrossRefGoogle Scholar
  11. 11.
    Heinzelman, W.B.: Application-Specific Protocol Architectures for Wireless Networks. Ph.D. Thesis, Massachusetts Institute of Technology, MIT (2000)Google Scholar
  12. 12.
    Muruganathan, S.D., Ma, D.C.F., Bhasin, R.I., Fapojuwo, A.O.: A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks. IEEE Communications Magazine 43, 8–13 (2005)CrossRefGoogle Scholar
  13. 13.
    Ghiasi, S., et al.: Optimal Energy Aware Clustering in Sensor Networks. MDPI Sensors 2(7), 40–50 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guangyan Huang
    • 1
  • Xiaowei Li
    • 1
  • Jing He
    • 2
  1. 1.Advanced Test Technology Lab., Institute of Computing TechnologyChinese Academy of SciencesBeijingP. R.China
  2. 2.Chinese Academy of Sciences Research Center on Data Technology and, Knowledge EconomyBeijingP. R. China

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