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Reseach Article

Lifetime Maximization in Wireless Sensor Networks based on using Data Compression

by Safa Khudair Leabi, Turki Younis Abdalla
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 11
Year of Publication: 2015
Authors: Safa Khudair Leabi, Turki Younis Abdalla
10.5120/21748-5004

Safa Khudair Leabi, Turki Younis Abdalla . Lifetime Maximization in Wireless Sensor Networks based on using Data Compression. International Journal of Computer Applications. 122, 11 ( July 2015), 45-51. DOI=10.5120/21748-5004

@article{ 10.5120/21748-5004,
author = { Safa Khudair Leabi, Turki Younis Abdalla },
title = { Lifetime Maximization in Wireless Sensor Networks based on using Data Compression },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 11 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 45-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number11/21748-5004/ },
doi = { 10.5120/21748-5004 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:19.743813+05:30
%A Safa Khudair Leabi
%A Turki Younis Abdalla
%T Lifetime Maximization in Wireless Sensor Networks based on using Data Compression
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 11
%P 45-51
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, the demand and development of multimedia product expands increasingly fast, sharing out networks bandwidth and appliances memory. Therefore, data compression theory becomes the major considerable for reducing datum volume so as to economize extra transmission bandwidth and hardware sharing. Energy limitations have become fundamental challenge for designing wireless sensor networks. Network lifetime represent the most important and interested metric. This paper proposes data compression methods for maximizing lifetime of the network. Two lossless compression methods are proposed for compressing patients ECG data. The first is Huffman coding and the second is arithmetic coding. Dijkstra routing has been used as the main routing protocol. A comparison has been made for the two compression methods. Simulations demonstrate that Huffman coding has superior performance against arithmetic coding. It shows an increase in network lifetime of about 63% while arithmetic coding shows lifetime increase of about 16. 76%. Results show the effectiveness of the Huffman coding method for maximizing WSNs lifetime.

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Index Terms

Computer Science
Information Sciences

Keywords

Wireless sensor networks network lifetime data compression ECG data Huffman coding arithmetic coding