An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks

The problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. By using a novel metric derived from the energy model in LEACH (W.B. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, in: Proce...

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Main Author: Loredana Arienzo
Format: Article
Language:English
Published: SpringerOpen 2010-01-01
Series:EURASIP Journal on Wireless Communications and Networking
Online Access:http://dx.doi.org/10.1155/2010/641632
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spelling doaj-bf87f541fc634e8fa8e3e9cef938a9d32020-11-24T21:44:28ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992010-01-01201010.1155/2010/641632An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor NetworksLoredana ArienzoThe problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. By using a novel metric derived from the energy model in LEACH (W.B. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, in: Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS '00), 2000) and aiming at an efficient resource solution, the approach adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimize the energy consumption of the tracking task. We layout a cluster-based architecture to address the limitations in computational power, battery capacity and communication capacities of the sensor devices. The computation of the posterior Cramer-Rao bound (PCRB) based on received signal strength measurements has been considered. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented particle filter, both in the centralized and in the distributed manner. Their performances are compared with the theoretical lower bound PCRB. To save energy, a node selection procedure based on greedy algorithms is proposed. The node selection problem is formulated as a cross-layer optimization problem and it is solved using greedy algorithms. http://dx.doi.org/10.1155/2010/641632
collection DOAJ
language English
format Article
sources DOAJ
author Loredana Arienzo
spellingShingle Loredana Arienzo
An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks
EURASIP Journal on Wireless Communications and Networking
author_facet Loredana Arienzo
author_sort Loredana Arienzo
title An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks
title_short An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks
title_full An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks
title_fullStr An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks
title_full_unstemmed An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks
title_sort information-theoretic approach for energy-efficient collaborative tracking in wireless sensor networks
publisher SpringerOpen
series EURASIP Journal on Wireless Communications and Networking
issn 1687-1472
1687-1499
publishDate 2010-01-01
description The problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. By using a novel metric derived from the energy model in LEACH (W.B. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, in: Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS '00), 2000) and aiming at an efficient resource solution, the approach adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimize the energy consumption of the tracking task. We layout a cluster-based architecture to address the limitations in computational power, battery capacity and communication capacities of the sensor devices. The computation of the posterior Cramer-Rao bound (PCRB) based on received signal strength measurements has been considered. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented particle filter, both in the centralized and in the distributed manner. Their performances are compared with the theoretical lower bound PCRB. To save energy, a node selection procedure based on greedy algorithms is proposed. The node selection problem is formulated as a cross-layer optimization problem and it is solved using greedy algorithms.
url http://dx.doi.org/10.1155/2010/641632
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