Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/11714
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dc.contributor.authorTuama, A.Y.en_US
dc.contributor.authorMohamed, M.A.en_US
dc.contributor.authorMuhammed, A.en_US
dc.contributor.authorHanapi, Z.M.en_US
dc.contributor.authorMohamed, R.R.en_US
dc.contributor.authorAbu Bakar, K.A.en_US
dc.date.accessioned2019-01-23T04:24:33Z-
dc.date.available2019-01-23T04:24:33Z-
dc.date.issued2018-
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/11714-
dc.description.abstractWireless Sensor Networks (WSNs) have emerged as one of the most promising wireless communication systems supporting wide variety of applications ranging from military tasks, healthcare, disaster prediction and indoor positioning. The low complexity and cost of the nodes result in constraints such as computational power, communication bandwidth and battery power. Energy consumption is one of the most critical to WSN. In WSN communication, data transmission is considered the largest contributor to total energy exhaustion and apparently, it is influenced by the size of the data. Favorably, data compression can be used to reduce the amount of data that requires to be transmitted and hence prolongs sensor's lifetime. In this study, we survey various approaches, issues and challenges to WSN efficiency related to data compression discuss the effect of the data size on the sensor efficiency and how data compression algorithms can be used to address small size data transmission. Finally, recent approaches are reviewed with highlighting of advantages and disadvantages of each solution. © Medwell Journals, 2018.
dc.language.isoenen_US
dc.titleRecent advances of data compression in Wireless Sensor Networken_US
dc.typeArticleen_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
Appears in Collections:UNITEN Scholarly Publication
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