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Alive Nodes Based Improved Low Energy Adaptive Clustering Hierarchy for Wireless Sensor Network

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 28)

Abstract

Energy efficiency is one of the important issues in the Wireless Sensor Networks (WSN). In this paper, a decentralized Alive Nodes based Low Energy Adaptive Clustering Hierarchy (AL-LEACH) is presented, that considers number of alive nodes in the network to elect the cluster heads. Alive nodes are used to dynamically compute weights of random numbers. Random number is one of the important parameters to elect cluster heads for the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Extensive simulations are carried out to compare our proposed approach AL-LEACH with Low Energy Adaptive Clustering Hierarchy (LEACH), Low energy adaptive clustering hierarchy with Deterministic Cluster-Head Selection (LDCHS) and Advanced LEACH routing protocol for wireless micro sensor networks (ALEACH). Simulation results show that AL-LEACH improves the network life time and number of packets received by Base Station (BS) through balanced energy consumption of the network.

Keywords

Improved LEACH Alive nodes Random number Balanced energy consumption Cluster head election Energy efficient routing Wireless sensor network 

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References

  1. 1.
    Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, p. 10. IEEE (2000)Google Scholar
  2. 2.
    Handy, M., Haase, M., Timmermann, D.: Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In: 4th International Workshop on Mobile and Wireless Communications Network, pp. 368–372. IEEE (2002)Google Scholar
  3. 3.
    Manzoor, B., Javaid, N., Rehman, O., Akbar, M., Nadeem, Q., Iqbal, A., Ishfaq, M.: Q-LEACH: A New Routing Protocol for WSNs. arXiv preprint arXiv:1303.5240 (2013)Google Scholar
  4. 4.
    Thakkar, A., Kotecha, K.: CVLEACH: Coverage based energy efficient LEACH Algorithm. International Journal of Computer Science and Network (IJCSN) 1 (2012)Google Scholar
  5. 5.
    Ali, M.S., Dey, T., Biswas, R.: ALEACH: Advanced LEACH routing protocol for wireless microsensor networks. In: International Conference on Electrical and Computer Engineering, ICECE 2008, pp. 909–914. IEEE (2008)Google Scholar
  6. 6.
    Thakkar, A., Kotecha, K.: WALEACH: Weight based energy efficient Advanced LEACH algorithm. Computer Science & Information Technology (CS & IT) 2(4)Google Scholar
  7. 7.
    Thakkar, A., Kotecha, K.: WCVALEACH: Weight and Coverage based energy efficient Advanced LEACH algorithm. Computer Science & Engineering 2(6) (2012)Google Scholar
  8. 8.
    Smaragdakis, G., Matta, I., Bestavros, A.: SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. Boston University Computer Science Department Research Lab (2004) (last accessed February 21, 2014)Google Scholar
  9. 9.
    Qiu, L., Wang, Y., Zhao, Y., Xu, D., Dan, Q., Zhu, J.: Wireless sensor networks routing protocol based on self-organizing clustering and intelligent ant colony optimization algorithm. In: 9th International Conference on Electronic Measurement & Instruments, ICEMI 2009, pp. 3–223. IEEE (2009)Google Scholar
  10. 10.
    Wang, A., Yang, D., Sun, D.: A clustering algorithm based on energy information and cluster heads expectation for wireless sensor networks. Computers & Electrical Engineering 38(3), 662–671 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Institute of TechnologyNirma UniversityAhmadabadIndia

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