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Enhancement in lifetime of sensor node using Data Reduction Technique in Wireless Sensor Network

by Nikhil Kumar Singh, Ankit Kasana, Vibhav Kumar Sachan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 11
Year of Publication: 2016
Authors: Nikhil Kumar Singh, Ankit Kasana, Vibhav Kumar Sachan
10.5120/ijca2016910802

Nikhil Kumar Singh, Ankit Kasana, Vibhav Kumar Sachan . Enhancement in lifetime of sensor node using Data Reduction Technique in Wireless Sensor Network. International Journal of Computer Applications. 145, 11 ( Jul 2016), 1-5. DOI=10.5120/ijca2016910802

@article{ 10.5120/ijca2016910802,
author = { Nikhil Kumar Singh, Ankit Kasana, Vibhav Kumar Sachan },
title = { Enhancement in lifetime of sensor node using Data Reduction Technique in Wireless Sensor Network },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 11 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number11/25319-2016910802/ },
doi = { 10.5120/ijca2016910802 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:48:29.233372+05:30
%A Nikhil Kumar Singh
%A Ankit Kasana
%A Vibhav Kumar Sachan
%T Enhancement in lifetime of sensor node using Data Reduction Technique in Wireless Sensor Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 11
%P 1-5
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper data compression is becoming more popular, because it helps to reduce the size.A number of clustering protocols have been explored in order to obtain the effective energy usage in WSNs. It is based on randomized rotation of the CHs to distribute the energy load among the sensor nodes evenly in the entire network. Each node elects itself as a CH based on a probabilistic scheme and broadcasts its availability to all the sensor nodes present in the area. The received signal strength is the prime parameter for determining the communication distance between the nodes. The CH performs aggregation of the packets received from all the nodes present in their cluster. Also, all the nodes get a chance to become the CH to balance the overall energy consumption across the network. The aim ofClustering is one of the important methods for prolonging the network lifetime in wireless sensor networks (WSNs). It involves grouping of sensor nodes into clusters and electing cluster heads (CHs) for all the clusters. CHs collect the data from respective cluster’s nodes and forward the aggregated data to base station.by using Huffman encoding techniques [1].

References
  1. Shrusti Porwal (2013), “Data Compression Methodologies for Lossless Data and Comparison between Algorithms” International Journal of Engineering Science and Innovative Technology (IJESIT)
  2. Ying Liang “Energy Adaptive Cluster-Head Selection for Wireless Sensor Networks” IEEE, December, 2005,
  3. Microsensor Networks", In Proc. 33rd HICS, 4-7 Jan, 20004-Anirooth Thonklin, W. Suntiamorntut “Load Balanced and Energy Efficient Cluster Head Election in Wireless Sensor Networks.
  4. Thein (29 January, 2010) “An Energy Efficient Cluster-Head Selection for Wireless Sensor Networks
  5. Vibhav Kumar Sachan, Syed Akhtar Imam and M T Beg. Article: Energy-Efficient Communication Methods in Wireless Sensor Networks: A Critical Review. International Journal of Computer Applications 39(17):35-48, February 2012
  6. Himanshu Sharma, Vibhav Kumar Sachan and Syed Akhtar Imam. Article: Energy Efficiency of the IEEE 802.15.4 Standard in Wireless Sensor Networks: Modeling and Improvement Perspectives. International Journal of Computer Applications 58(9):12-19, November 2012
  7. Syed Akhtar Imam, Vibhav Kumar Sachan and Shivani Singh. Article: Data Aggregation based Cooperative MIMO System for Wireless Sensor Networks: Performance Analysis. International Journal of Computer Applications 90(4):1-7, March 2014.
  8. Syed Akhtar Imam, Vibhav Sachan and Shivani Singh. Article: Performance Analysis of Different Diversity Schemes for Energy Efficient Wireless Sensor Network. IJCA Proceedings on 4th International IT Summit Confluence 2013
  9. Vibhav Kumar Sachan, Richa Maheshwari and Syed Akhtar Imam. Article: Energy Efficient Wireless Sensor Networks using Co-operative MIMO: A Technical Review. International Journal of Computer Applications 135(11):20-27, February 2016
  10. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: a survey,” Computer Networks, vol. 38, no. 4, pp. 393–422, 2002.
  11. J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,”Computer Networks, vol. 52, no. 12, pp. 2292–2330, 2008.
  12. C. F. Hsin and M. Liu, “Randomly duty-cycled wireless sensor networks:dynamic of coverage,” IEEE Trans. Wireless Commun., vol. 5, no. 11,pp. 3182–3192, 2006
  13. Pratyay Kuila (2012) “An energy balanced distributed clustering and routing algorithm for Wireless Sensor Networks”
  14. W. Suntiamorntut “Load Balanced and Energy Efficient Cluster Head Election in Wireless Sensor Networks
  15. M. J. Handy “Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-Head Selection” IEEE, September, 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Wireless sensor network (WSN) cluster Head (CH) Sensor node Huffman coding.

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