Skip to main content

Lifetime Enhancement of a Node Using I—Leach Protocol in WSN

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 668))

Abstract

The developments in the place of wireless networks and their integration in unique sectors effectively caused the emergence of a new own family of networks known as wireless sensor networks. The various demanding situations the maximum studied in WSN are the energy intake and the life of the nodes. An excellent node placement deploying is one of the issues which may be exploited to reap the maximum most effective layout for saving the strength. This paper proposes improved leach (I—leach) protocol which increases network lifetime, and it will improve the quality of QoS. The experimental results show that the proposed technique is giving better results in terms of energy consumption than existing techniques.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. N.K. Jassi, S.S Wraich, An enhanced K-means clustering technique with Hopfields artificial neural network based on reactive clustering protocol, in International Conference—Confluence the Next Generation Information Technology Summit-2014 978-1-4799-4236-7/14/IEEE

    Google Scholar 

  2. A. Das, G. Das, Distributed extraction and a novel association rule mining mechanism for WSN: an empirical analysis. ICETACS-2013,978-1-4673-5250-5/13/2013-IEEE

    Google Scholar 

  3. C. Zhao, W. Zhang, Y. Yang, S. Yao, Treelet-based clustered compressive data aggregation for wireless sensor networks. IEEE Trans. Veh. Technol. 0018-9545© 2013

    Google Scholar 

  4. M.B. Thaker, U. Nagaraj, P.D. Ganjewar, Data reduction techniques in wireless sensor network: a servey. Int. J. Innovative Res Comput Commun. Eng. 2(11) (2014)

    Google Scholar 

  5. Y. Singh, S. Saha, U. Chugh, C. Gupta, Distributed event detection in wireless sensor networks for forest fires, 15th International Conference on Computing Modelling and Simulation-2013 978-0-7695-4994-1/13/IEEE

    Google Scholar 

  6. S. Rashid, U. Akram, S. Qaisar, S.A. Khan, E. Felemban, Wireless sensor network for distributed event detection based on machine learning, in IEEE International Conference on Internet of Things, Green Computing and Communications and Cyber-Physical-Social Computing-2014,978-1-4799-5967-9/14/IEEE

    Google Scholar 

  7. G. Sahni, S. Sharma, Study of various anomalies detection methodologies in wireless sensor network. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 3(5), May 2013, ISSN:2277128X

    Google Scholar 

  8. X. Liu, A novel transmission range adjustment strategy for energy hole avoiding in wireless sensor networks. J. Netw. Comput. Appl. 67, 43–52 (2016)

    Article  Google Scholar 

  9. I.F. Akyildiz et al., A survey on sensor networks. IEEE Commun. Mag. 40(8), 102–114 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to D. Venkatesh .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Venkatesh, D., Subramanyam, A. (2018). Lifetime Enhancement of a Node Using I—Leach Protocol in WSN. In: Dash, S., Naidu, P., Bayindir, R., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 668. Springer, Singapore. https://doi.org/10.1007/978-981-10-7868-2_11

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7868-2_11

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7867-5

  • Online ISBN: 978-981-10-7868-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics