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  5. Compression in wireless sensor networks: A survey and comparative evaluation
 
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Compression in wireless sensor networks: A survey and comparative evaluation

Author(s)
Razzaque, M. A.  
Bleakley, Chris J.
Dobson, Simon  
Uri
http://hdl.handle.net/10197/7031
Date Issued
2013-11-01
Date Available
2015-09-15T15:42:41Z
Abstract
Wireless sensor networks (WSNs) are highly resource constrained in terms of power supply, memory capacity, communication bandwidth, and processor performance. Compression of sampling, sensor data, and communications can significantly improve the efficiency of utilization of three of these resources, namely, power supply, memory and bandwidth. Recently, there have been a large number of proposals describing compression algorithms for WSNs. These proposals are diverse and involve different compression approaches. It is high time that these individual efforts are put into perspective and a more holistic view taken. In this article, we take a step in that direction by presenting a survey of the literature in the area of compression and compression frameworks in WSNs. A comparative study of the various approaches is also provided. In addition, open research issues, challenges and future research directions are highlighted.
Sponsorship
Higher Education Authority
Type of Material
Journal Article
Publisher
Association for Computing Machinery
Journal
ACM Transactions on Sensor Networks
Volume
10
Issue
1
Start Page
5:1
End Page
5:44
Copyright (Published Version)
2013 ACM
Subjects

Algorithms

Measurement

Performance

Wireless sensor netwo...

Compression

DOI
10.1145/2528948
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Compression_in_Wireless_Sensor_Networks_a_Survey_and_the_Road_Ahead.pdf

Size

1.46 MB

Format

Adobe PDF

Checksum (MD5)

6a787f2ef0f575e9af11a7ab20c0daed

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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