Optimized Low-Energy Adaptive Clustering Hierarchy in Wireless Sensor Network

  • Sumit PundirEmail author
  • Mohammad Wazid
  • Ayan Bakshi
  • Devesh Pratap Singh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1162)


Energy which drives the whole world is also required for the propitious technology called wireless sensor network (WSN), which is the driving force of many helpful applications in many areas like health, environment, and industry monitoring, mainly for detecting the threats. The ease of portability, availability, accuracy, and advancement in wireless communication has made it popular among the masses. Sensing nodes are set up in a geographical area of interest, and then, these nodes sense the environmental physical phenomenon and accumulate the information and transfer it to the sink (base station) for application specific action. One of the major concerns with WSN is the network lifetime because of the battery-powered sensing devices. It is one of the most challenging problems which is related with all the issues present in the WSN. The recharge of the sensing devices and prolonging the network lifetime can be achieved through energy harvesting techniques. The primary goal is to enhance the lifetime of the battery-powered sensors and prolong the network lifetime. Numerous of routing protocols have been proposed by the researchers like many versions of LEACH protocols, RPL, 6LowPAN, etc. Here, we propose optimized form of LEACH routing protocol which improves the lifetime of the network, and the simulation results show that the proposed work has improved the network lifetime and stability of the protocol compared with the other existing techniques.


Network lifetime Optimized LEACH Wireless sensor networks 


  1. 1.
    Manjeshwar, A., Agarwal, D.P.: TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. In: Presented in 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing (2001)Google Scholar
  2. 2.
    Riga, N., Bestavros, A., Matta, I.: DIP: Density Inference Protocol for wireless sensor networks and its applications to density unbiased statistics. Technical Report BUCS-TR-2004-023 (2004)Google Scholar
  3. 3.
    Maurya, S., Jain, V.K.: Fuzzy Based Energy Efficient Sensor Network Protocol for Precision Agriculture (2006)Google Scholar
  4. 4.
    Wu, H., Zhao, C., Zhu, L.: Study on an energy-aware routing algorithm for agriculture WSN. Indonesian J Electr. Comput. Sci. 11(7) (2013)Google Scholar
  5. 5.
    Lu, H., Liao,Y.M.: Multipurpose watermarking for image authentication and protection. IEEE Trans. Image Process. 10, 1579–1592 (2001)Google Scholar
  6. 6.
    Smaragdakis, G., Matta, I., Bestavros, A.: SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. In: Second International Workshop in Sensor and Actor Network Protocols and Applications (SNPA) (2004)Google Scholar
  7. 7.
    Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocols for wireless microsensor networks. In: Proceedings of Hawaiian international conference on systems science (2000)Google Scholar
  8. 8.
    Fu, C., Wei, W., Wei, A., Jiang, Z. (2013). An energy balanced algorithm of LEACH protocol in WSN. Int. J. Comput. Sci. Issues (IJCSI) 10(1) (2013)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  • Sumit Pundir
    • 1
    Email author
  • Mohammad Wazid
    • 1
  • Ayan Bakshi
    • 1
  • Devesh Pratap Singh
    • 1
  1. 1.Department of Computer Science and EngineeringGraphic Era Deemed to be UniversityDehradunIndia

Personalised recommendations