Performance Comparison of Data Reduction Techniques for Wireless Multimedia Sensor Network Applications

With the increased use of smart phones, Wireless Multimedia Sensor Networks (WMSNs) will have opportunities to deploy such devices in several contexts for data collection and processing. While smart phones come with richer resources and can do complex processing, their battery is still limited. Back...

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Bibliographic Details
Published inInternational journal of distributed sensor networks Vol. 2015; no. 8; p. 873495
Main Authors Sarisaray-Boluk, Pinar, Akkaya, Kemal
Format Journal Article
LanguageEnglish
Published London, England Hindawi Publishing Corporation 01.01.2015
SAGE Publications
Sage Publications Ltd. (UK)
John Wiley & Sons, Inc
Wiley
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Online AccessGet full text
ISSN1550-1329
1550-1477
1550-1477
DOI10.1155/2015/873495

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Summary:With the increased use of smart phones, Wireless Multimedia Sensor Networks (WMSNs) will have opportunities to deploy such devices in several contexts for data collection and processing. While smart phones come with richer resources and can do complex processing, their battery is still limited. Background subtraction (BS) and compression techniques are common data reduction schemes, which have been used for camera sensors to reduce energy consumption in WMSNs. In this paper, we investigate the performance of various BS algorithms and compression techniques in terms of computation and communication energy, time, and quality. We have picked five different BS algorithms and two compression techniques and implemented them in an Android platform. Considering the fact that these BS algorithms will be run within the context of WMSNs where the data is subject to packet losses and errors, we also investigated the performance in terms of packet loss ratio in the network under various packet sizes. The experiment results indicated that the most energy-efficient BS algorithm could also provide the best quality in terms of the foreground detected. The results also indicate that data reduction techniques including BS algorithms and compression techniques can provide significant energy savings in terms of transmission energy costs.
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ISSN:1550-1329
1550-1477
1550-1477
DOI:10.1155/2015/873495