skip to main content
10.1145/1143549.1143842acmconferencesArticle/Chapter ViewAbstractPublication PagesiwcmcConference Proceedingsconference-collections
Article

An algorithm for electing cluster heads based on maximum residual energy

Published:03 July 2006Publication History

ABSTRACT

One of the main challenges in wireless sensor networks is to obtain long system lifetime. We propose an algorithm for electing the cluster head node based on the maximum residual energy for the purpose of even distribution of energy consumption in the overall network and obtaining the longest network lifetime. To maintain the original performance of the network, the lifetime is suggested to be expressed as to both the maximum last node dying time and the minimum time difference between the last node dying and the first node dying. The key parameter — the electing coefficient (θ) was obtained and evaluated. The optimal θ value is related to number of nodes, energy consumption of cluster members (ECCM), and energy consumption of the cluster head (ECCH). θ descends when number of nodes and ECCM decrease, and when ECCH increases. However, when energy consumptions of the cluster head and cluster members change proportionally, θ seems to be affected slightly. Results show that network lifetime can be prolonged when cluster heads are elected with the optimal θ value.

References

  1. Asada G, Dong M, Lin TS, Newberg F, Pottie G, Kaiser WJ. Wireless integrated network sensors: low power systems on a chip. Proceedings of the 24th European Solid-State Circuits Conference, (ESSCIRC 98), Editions Frontieres: Paris, 1998, pp. 9--16Google ScholarGoogle Scholar
  2. Chalermek Intanagonwiwat, Ramesh Govindan, Deborah Estrin, John Heidemann, Fabio Silva. Directed diffusion for wireless sensor networking. IEEE/ACM Transactions on Networking (TON), 2003, 11(1): 2--16 Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Chunhung Richard Lin and Mario Gerla. Adaptive clustering for mobile wireless networks. IEEE Journal on Selected Areas in Communications, 15(7):1265--1275, Sep 1997 Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Deborah Estrin, Ramesh Govindan, John Heidemann, Satish Kumar. Next Century Challenges: Scalable Coordination in Sensor Networks. In Proc. of the ACM International Conference on Mobile Computing and Networking (MOBICOM), August 1999 Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Di Tian and Nicolas D. Georganas. A node scheduling scheme for energy for energy conservation in large wireless sensor networks. Wireless Communications and Mobile Computing, 2003; 3: 271--290Google ScholarGoogle Scholar
  6. Dong MJ, Geoffrey Yung K, Kaiser WJ. Low power signal processing architectures for network microsensors. 1997 International Symposiums on Low Power Electronics and Design, Digest of Technical Papers (1997), 1997, pp. 173--177 Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Fan Ye, Gary Zhong, Songwu Lu, Lixia Zhang. PEAS: A robust energy conserving protocol for long-lived sensor networks. Proc. of the 10th IEEE International Conference on Network Protocols (ICNP'02), 2002 Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. http://www.isi.edu/nsnam/ns/Google ScholarGoogle Scholar
  9. Indranil Gupta, Denis Riordan, Srinivas Sampalli. Cluster-Head Election Using Fuzzy Logic for Wireless Sensor Networks. cnsr, pp. 255--260, 3rd Annual Communication Networks and Services Research Conference (CNSR'05), 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Katja Schwieger, Heinrich Nuszkowski, and Gerhard Fettweis. Analysis of Node Energy Consumption in Sensor Networks. European Workshop on Wireless Sensor Networks 2004: 94--105Google ScholarGoogle Scholar
  11. LIANG Ying, YU Haibin. Energy Adaptive Cluster-Head Selection for Wireless Sensor Networks. pdcat, pp. 634--638, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Matthew Ettus. System capacity, latency, and power consumption in multihop-routed SS-CDMA wireless networks. The Proceedings Radio and Wireless Conf. (RAWCON), Colorado Springs, CO, 1998, Aug.: pp. 55--58Google ScholarGoogle ScholarCross RefCross Ref
  13. Ossama Younis, Sonia Fahmy. HEED: a hybrid, energy efficient, distributed clustering approach for ad hoc sensor networks. IEEE INFOCOM, 2004 Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Porret A, Melly T, Enz CC, Vittoz EA. A lower-power lowvoltage transceiver architecture suitable for wireless distributed sensor network. Proceeding of IEEE International Symposium on Circuits and Systems '00, Vol. 1, Geneva, 2000, pp. 56--59Google ScholarGoogle Scholar
  15. Rabaey JM, Ammer MJ, da Silva JL. Roundy DPS, PicoRadio supports ad hoc ultra-low power wireless networking. IEEE Computer Magzine, 2000, July: pp.42--48 Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Suman Banerjee, Samir Khuller. A Clustering Scheme for Hierarchical Control in Multi-hop Wireless Networks. In Proc. of IEEE INFOCOM, April 2001Google ScholarGoogle Scholar
  17. Tanner C. B. Plant temperature. Agronomy Journal, 1963, 55:210--211Google ScholarGoogle ScholarCross RefCross Ref
  18. Wendi B, Heinzelman, Anantha P, Chandrakasan, Hari Balakrishnan. An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 2002, 1(4):660--670 Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Ya Xu, Solomon Bien, Yutaka Mori, John Heidemann, Deborah Estrin. Topology control protocol to conserve energy in wireless ad hoc networks. Technical Report 6, University of California, Los Angeles, Center for Embedded Network Computing (2003), submitted for publicationGoogle ScholarGoogle Scholar

Index Terms

  1. An algorithm for electing cluster heads based on maximum residual energy

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      IWCMC '06: Proceedings of the 2006 international conference on Wireless communications and mobile computing
      July 2006
      2006 pages
      ISBN:1595933069
      DOI:10.1145/1143549

      Copyright © 2006 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 3 July 2006

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • Article

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader