On asynchronous training in sensor networks
Due to their small form factor and modest energy budget it is infeasible to endow individual sensors with GPS capabilities. Yet, numerous applications require sensors to have a coarse-grain location awareness. The task of acquiring this coarse-grain location awareness is referred to as training. The...
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Rinton Press, USA
2007
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| Online Access: | http://eprints.utm.my/id/eprint/17872/ http://dl.acm.org/citation.cfm?id=2010536&CFID=282616781&CFTOKEN=69784935 |
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my.utm.178722017-10-23T13:25:38Z http://eprints.utm.my/id/eprint/17872/ On asynchronous training in sensor networks Qing Wen, Xu Ishak, Ruzana Olariu, Stephan Salleh, Shaharuddin HE Transportation and Communications Q Science (General) QA75 Electronic computers. Computer science Due to their small form factor and modest energy budget it is infeasible to endow individual sensors with GPS capabilities. Yet, numerous applications require sensors to have a coarse-grain location awareness. The task of acquiring this coarse-grain location awareness is referred to as training. The main contribution of this work is to propose a fully asynchronous training protocol for massively-deployed sensor networks. The sensors wake up according to their internal clock and are not engaging in synchronization with the sink. Our protocol is lightweight and simple to implement. We show analytically that in spite of the lack of synchronization, individual sensors are trained energy-efficiently. The analytical results have been confirmed by simulation. Rinton Press, USA 2007-03 Article PeerReviewed Qing Wen, Xu and Ishak, Ruzana and Olariu, Stephan and Salleh, Shaharuddin (2007) On asynchronous training in sensor networks. Journal of Mobile Multimedia, 3 (1). pp. 34-46. http://dl.acm.org/citation.cfm?id=2010536&CFID=282616781&CFTOKEN=69784935 |
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HE Transportation and Communications Q Science (General) QA75 Electronic computers. Computer science |
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HE Transportation and Communications Q Science (General) QA75 Electronic computers. Computer science Qing Wen, Xu Ishak, Ruzana Olariu, Stephan Salleh, Shaharuddin On asynchronous training in sensor networks |
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Due to their small form factor and modest energy budget it is infeasible to endow individual sensors with GPS capabilities. Yet, numerous applications require sensors to have a coarse-grain location awareness. The task of acquiring this coarse-grain location awareness is referred to as training. The main contribution of this work is to propose a fully asynchronous training protocol for massively-deployed sensor networks. The sensors wake up according to their internal clock and are not engaging in synchronization with the sink. Our protocol is lightweight and simple to implement. We show analytically that in spite of the lack of synchronization, individual sensors are trained energy-efficiently. The analytical results have been confirmed by simulation. |
| format |
Article |
| author |
Qing Wen, Xu Ishak, Ruzana Olariu, Stephan Salleh, Shaharuddin |
| author_facet |
Qing Wen, Xu Ishak, Ruzana Olariu, Stephan Salleh, Shaharuddin |
| author_sort |
Qing Wen, Xu |
| title |
On asynchronous training in sensor networks |
| title_short |
On asynchronous training in sensor networks |
| title_full |
On asynchronous training in sensor networks |
| title_fullStr |
On asynchronous training in sensor networks |
| title_full_unstemmed |
On asynchronous training in sensor networks |
| title_sort |
on asynchronous training in sensor networks |
| publisher |
Rinton Press, USA |
| publishDate |
2007 |
| url |
http://eprints.utm.my/id/eprint/17872/ http://dl.acm.org/citation.cfm?id=2010536&CFID=282616781&CFTOKEN=69784935 |
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