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On the Optimal Density for Real-Time Data Gathering of Spatio-Temporal Processes in Sensor Networks

Cristescu, Răzvan and Vetterli, Martin (2005) On the Optimal Density for Real-Time Data Gathering of Spatio-Temporal Processes in Sensor Networks. In: IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005. IEEE , Piscataway, NJ, pp. 159-164. ISBN 0-7803-9201-9. https://resolver.caltech.edu/CaltechAUTHORS:20160414-155253312

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Abstract

We consider sensor networks that measure spatio-temporal correlated processes. An important task in such settings is the reconstruction at a certain node, called the sink, of the data at all points of the field. We consider scenarios where data is time critical, so delay results in distortion, or suboptimal estimation and control. For the reconstruction, the only data available to the sink are the values measured at the nodes of the sensor network, and knowledge of the correlation structure: this results in spatial distortion of reconstruction. Also, for the sake of power efficiency, sensor nodes need to transmit their data by relaying through the other network nodes: this results in delay, and thus temporal distortion of reconstruction if time critical data is concerned. We study data gathering for the case of Gaussian processes in one- and two-dimensional grid scenarios, where we are able to write explicit expressions for the spatial and time distortion, and combine them into a single total distortion measure. We prove that, for various standard correlation structures, there is an optimal finite density of the sensor network for which the total distortion is minimized. Thus, when power efficiency and delay are both considered in data gathering, it is useless from the point of view of accuracy of the reconstruction to increase the number of sensors above a certain threshold that depends on the correlation structure characteristics.


Item Type:Book Section
Related URLs:
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http://dx.doi.org/10.1109/IPSN.2005.1440918DOIPaper
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1440918PublisherPaper
Additional Information:© 2005 IEEE.
Record Number:CaltechAUTHORS:20160414-155253312
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20160414-155253312
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:66194
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:14 Apr 2016 22:58
Last Modified:03 Oct 2019 09:54

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