Detection and Localization Sensor Assignment with Exact and Fuzzy Locations

Authors:
Hosam Rowaihy;Matthew P. Johnson;Diego Pizzocaro;Amotz Bar-Noy;Lance Kaplan;Thomas Porta;Alun Preece
Affiliations:
Dept. of Computer Science and Engineering, Pennsylvania State University, USA;Dept. of Computer Science, Graduate Center, City University of New York, USA;School of Computer Science, Cardiff University, UK;Dept. of Computer Science, Graduate Center, City University of New York, USA;U.S. Army Research Laboratory, USA;Dept. of Computer Science and Engineering, Pennsylvania State University, USA;School of Computer Science, Cardiff University, UK
Venue:
DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
Year:
2009

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Abstract

Sensor networks introduce new resource allocation problems in which sensors need to be assigned to the tasks they best help. Such problems have been previously studied in simplified models in which utility from multiple sensors is assumed to combine additively. In this paper we study more complex utility models, focusing on two particular applications: event detection and target localization. We develop distributed algorithms to assign directional sensors of different types to multiple simultaneous tasks using exact location information. We extend our algorithms by introducing the concept of fuzzy location which may be desirable to reduce computational overhead and/or to preserve location privacy. We show that our schemes perform well using both exact or fuzzy location information.