Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Acoustic sensor network design for position estimation

Acoustic sensor network design for position estimation In this article, we develop tractable mathematical models and approximate solution algorithms for a class of integer optimization problems with probabilistic and deterministic constraints, with applications to the design of distributed sensor networks that have limited connectivity. For a given deployment region size, we calculate the Pareto frontier of the sensor network utility at the desired probabilities for d -connectivity and k -coverage. As a result of our analysis, we determine (1) the number of sensors of different types to deploy from a sensor pool, which offers a cost vs. performance trade-off for each type of sensor, (2) the minimum required radio transmission ranges of the sensors to ensure connectivity, and (3) the lifetime of the sensor network. For generality, we consider randomly deployed sensor networks and formulate constrained optimization technique to obtain the localization performance. The approach is guided and validated using an unattended acoustic sensor network design. Finally, approximations of the complete statistical characterization of the acoustic sensor networks are given, which enable average network performance predictions of any combination of acoustic sensors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Sensor Networks (TOSN) Association for Computing Machinery

Acoustic sensor network design for position estimation

Loading next page...
 
/lp/association-for-computing-machinery/acoustic-sensor-network-design-for-position-estimation-0ayTlBsQxj
Publisher
Association for Computing Machinery
Copyright
Copyright © 2009 by ACM Inc.
ISSN
1550-4859
DOI
10.1145/1525856.1525859
Publisher site
See Article on Publisher Site

Abstract

In this article, we develop tractable mathematical models and approximate solution algorithms for a class of integer optimization problems with probabilistic and deterministic constraints, with applications to the design of distributed sensor networks that have limited connectivity. For a given deployment region size, we calculate the Pareto frontier of the sensor network utility at the desired probabilities for d -connectivity and k -coverage. As a result of our analysis, we determine (1) the number of sensors of different types to deploy from a sensor pool, which offers a cost vs. performance trade-off for each type of sensor, (2) the minimum required radio transmission ranges of the sensors to ensure connectivity, and (3) the lifetime of the sensor network. For generality, we consider randomly deployed sensor networks and formulate constrained optimization technique to obtain the localization performance. The approach is guided and validated using an unattended acoustic sensor network design. Finally, approximations of the complete statistical characterization of the acoustic sensor networks are given, which enable average network performance predictions of any combination of acoustic sensors.

Journal

ACM Transactions on Sensor Networks (TOSN)Association for Computing Machinery

Published: May 1, 2009

There are no references for this article.