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Power Saving Clustering Algorithm For Communication Of Wireless Sensor Network

Authors: Ajay Bisen, Ankita R.Mowar

Published in: IJRRETAS, Volume 2, Issue 6, pp. 1-4 (01 Jun 2016)

Impact Factor: 2.3 (2016)

License: CC BY 4.0 CC BY 4.0 (Open Access)

Certificate: View Certificate

Abstract

We have explored in this survey paper how multihop wireless energy transfer standard can be utilize to increase the lifetime of low-power networks, by charge nodes in a further convenient manner. In meticulous, we have proposed fusion clustering based optimization model to reduce the number of required chargers while taking into explanation the energy-demand of the nodes, the increasing energy loss that happen throughout a transfer and the ability of the chargers. As predictable, fusion clustering energy transfer enable us to decrease the number of chargers essential to gratify the energy-demand of each node. Our proposed model with heterogeneous WSN with its topology to have superior energy proficient and growing lifetime network may be examine. It improves the proposed approach to differ the range of the multi-hop zone dynamically by allowing for residual energy of each node. Our technique based on centralized and distributed clustering.

Keywords
  • Power Saving Clustering Algorithm For Communication Of Wireless Sensor Network
References
  1. Liguang Xie Yi Shi Y. Thomas Hou? Wenjing Lou Hanif D. Sherali Scott F. Midkiff ,” On Renewable Sensor Networks with Wireless Energy Transfer: The Multi-Node Case” Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)- 2012 .
  2. Liu Xiang, Student Member, IEEE, Jun Luo, Member, IEEE, and Catherine Rosenberg, Fellow, IEEE ,” Compressed Data Aggregation: Energy Efficient and High Fidelity Data Collection ” Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2011 8th Annual IEEE Communications Society Conference on. ISSN (Online ): 2455-4723
  3. Jin-Shyan Lee, Wei-Liang Cheng, “Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy Predication” IEEE SENSORS JOURNAL, VOL. 12, NO. 9, SEPTEMBER 2012.
  4. Mr. Guruprasad U, Mr. Jenne Hanumanthu, Dr. G.A.E. Satish Kumar,” Cluster head selection scheme using fuzzy based prediction for wireless sensor networks based on leach-ere algorithm’ (NCDATES-09 th & 10th January 2015).
  5. Jiping Xiong, Member, IEEE, Jian Zhao and Lei Chen,” Efficient Data Gathering in Wireless Sensor Networks Based on Matrix Completion and Compressive Sensing” IEEE Communications Letters,2013.
  6. Marco F. Duarte, Godwin Shen, Antonio Ortega and Richard G. Baraniuk, “Signal compression in wireless sensor networks,” Phil. Trans. R.Soc.A, Jan 2012, pp. 118-135.
  7. D.L.Donoho, “Compressed Sensing,” IEEE Transactions. Information Theory, vol.52, no.4, April 2006, pp. 1289-1306.
  8. E.J.Candes, “Compressive Sampling,” International Congress of Mathematicians, vol.3, pp. 1433-1452, Madrid, Spain, 2006.
  9. R.Berinde, P.Indyk, “Sparse recovery using sparse random matrices,” MIT-CSAIL Technical Report, 2008
How to Cite
APA: Bisen, A., & R.Mowar, A. (2016). Power Saving Clustering Algorithm For Communication Of Wireless Sensor Network. International Journal for Rapid Research in Engineering Technology & Applied Science, 2(6), 1–4. https://ijrretas.com/research-paper/power-saving-clustering-algorithm-for-communication-of-wireless-sensor-network
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  • Novel Fusion Based Multi Level Clustering For Power Saving In Communication Of Wireless Sensor Network2016 • Vol. 2, Issue 7

Download Paper

Paper Id: IJRRETAS32

Publish Date: 2016-06-01

ISSN: 2455-4723

Publisher Name: ijrretas

About IJRRETAS

ijrretas is a leading open-access, peer-reviewed journal dedicated to advancing research in applied sciences and engineering. We provide a global platform for researchers to disseminate innovative findings and technological breakthroughs.

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2455-4723
Established
2015

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