Information Processing in Sensor Networks: Second by Daniel Marco, Enrique J. Duarte-Melo, Mingyan Liu, David L.

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By Daniel Marco, Enrique J. Duarte-Melo, Mingyan Liu, David L. Neuhoff (auth.), Feng Zhao, Leonidas Guibas (eds.)

This quantity comprises the complaints of the second overseas Workshop on details Processing in Sensor Networks (IPSN 2003). The workshop used to be held on the Palo Alto examine heart (PARC), Palo Alto, California, on April 22–23, 2003. Informationprocessinginsensornetworksisaninterdisciplinaryresearcharea with deep connections to sign processing, networking and protocols, databases and knowledge administration, in addition to disbursed algorithms. as a result of - vances in MEMS microsensors, instant networking, and embedded processing, advert hoc networks of sensors have gotten more and more on hand for advertisement andmilitaryapplicationssuchasenvironmentalmonitoring(e.g.,tra?c,habitat, security), commercial sensing and diagnostics (e.g., factories, appliances), inf- constitution upkeep (e.g., strength grids, water distribution, waste disposal), and battle?eld expertise (e.g., multitarget tracking). From the engineering and computing viewpoint, sensor networks became a wealthy resource of difficulties in communique protocols, sensor tasking and keep watch over, sensor fusion, disbursed databases and algorithms, probabilistic reasoning, system/software structure, layout methodologies, and evaluate metrics. This workshop took a systemic method of handle crosslayer concerns, from the actual sensor layer to the sensor sign processing and networking degrees after which the entire technique to the functions. Following the winning 1st Workshop on Collaborative sign and Inf- mation Processing in Sensor Networks at PARC in 2001, this new workshop introduced jointly researchers from academia, undefined, and govt to p- despatched and talk about contemporary paintings referring to a number of points of sensor networks equivalent to info association, querying, routing, and self-organization, with an emphasis at the high-level info processing projects that those networks are designed to perform.

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Additional resources for Information Processing in Sensor Networks: Second International Workshop, IPSN 2003, Palo Alto, CA, USA, April 22–23, 2003 Proceedings

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They show that there is a critical combination of sensing and communication needed to ensure that multiple targets can be tracked satisfactorily by a sensor network. In [15], Li, Wong et al. tackle the problem of distinguishing between multiple targets, describing and developing several target classification mechanisms. Fang, Zhao and Guibas describe a distributed mechanism for counting the number of targets in a given field in [9]. In the context of these related works, we should emphasize that our attention is primarily focused on single-target tracking.

C. Cho, “Grid Coverage of Surveillance and Target location in Distributed Sensor Networks” To appear in IEEE Transaction on Computers, May 2002. 11. R. Bejar, B. Krishnamachari, C. Gomes, and B. Selman, “Distributed constraint satisfaction in a wireless sensor tracking system,” Workshop on Distributed Constraint Reasoning, International Joint Conference on Artificial Intelligence, Seattle, Washington, August 2001. 12. Jung, B. S. “Tracking Targets using Multiple Robots: The Effect of Environment Occlusion”, Autonomous Robots, 2002.

2000. edu/˜bkrishna/ 2 Abstract. We study the tradeoffs involved in the energy-efficient localization and tracking of mobile targets by a wireless sensor network. Our work focuses on building a framework for evaluating the fundamental performance of tracking strategies in which only a small portion of the network is activated at any point in time. We first compare naive network operation with random activation and selective activation. In these strategies the gains in energy-savings come at the expense of increased uncertainty in the location of the target, resulting in reduced quality of tracking.

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