2006 IEEE International Conference on Communications 2006
DOI: 10.1109/icc.2006.254733
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Spatio-temporal Characteristics of Point and Field Sources in Wireless Sensor Networks

Abstract: Abstract-Wireless Sensor Networks (WSN) are comprised of densely deployed sensor nodes collaboratively observing and communicating extracted information about a physical phenomenon. Dense deployment of sensor nodes makes the sensor observations highly correlated in the space domain. In addition, consecutive samples obtained by a sensor node are also temporally correlated for the applications involving the observation of the variation of a physical phenomenon. Based on the physical characteristics and dispersio… Show more

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Cited by 43 publications
(45 citation statements)
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“…Consider that the more severely a process is oversampled, the better suppression-based algorithms will appear to perform. There exists a body of literature that explicitly examines environmental relationships in the context of sensor networks (e.g., [28], [29]), and in the future we plan to use these relationships as a predictor of algorithmic performance.…”
Section: Discussionmentioning
confidence: 99%
“…Consider that the more severely a process is oversampled, the better suppression-based algorithms will appear to perform. There exists a body of literature that explicitly examines environmental relationships in the context of sensor networks (e.g., [28], [29]), and in the future we plan to use these relationships as a predictor of algorithmic performance.…”
Section: Discussionmentioning
confidence: 99%
“…A salient feature of sensor networks is that data collected by the neighboring senor nodes may carry redundant information due to the spatio-temporal correlation characteristics of the physical medium being sensed [22], [23], such as the temperature and humidity sensors in a similar geographic region or magnetometric sensors tracking a moving vehicle.…”
Section: B Data Aggregation Modelmentioning
confidence: 99%
“…Assuming that the point source is at the center of the coordinate axis [7], the sensor node situated at location (x, y) receives the signal given by…”
Section: Modeling Of Observed Event Signalmentioning
confidence: 99%
“…Here, we adopt the point source model [7] for event signal, and then we introduce the model for the event signal reconstruction. Note that, event signal reconstruction analysis introduced in this paper can be directly extended to the field source case.…”
Section: Reconstruction Of Observed Event Signalmentioning
confidence: 99%