Fault-tolerant target localization in sensor networks

Authors:
Min Ding;Fang Liu;Andrew Thaeler;Dechang Chen;Xiuzhen Cheng
Affiliations:
Computer Science Department, The George Washington University, Washington, DC;Computer Science Department, The George Washington University, Washington, DC;Computer Science Department, The George Washington University, Washington, DC;Division of Epidemiology and Biostatistics, Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, Bethesda, MD;Computer Science Department, The George Washington University, Washington, DC
Venue:
EURASIP Journal on Wireless Communications and Networking
Year:
2007

Citing 13
Cited 6

Wireless sensor networks for habitat monitoring

WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Lightweight sensing and communication protocols for target enumeration and aggregation

Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Energy-Aware Target Localization in Wireless Sensor Networks

PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks

ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
Tracking a moving object with a binary sensor network

Proceedings of the 1st international conference on Embedded networked sensor systems
Fault Tolerance in Collaborative Sensor Networks for Target Detection

IEEE Transactions on Computers
Sensor deployment and target localization in distributed sensor networks

ACM Transactions on Embedded Computing Systems (TECS)
iTPS: an improved location discovery scheme for sensor networks with long-range beacons

Journal of Parallel and Distributed Computing
Dynamic agent classification and tracking using an ad hoc mobile acoustic sensor network

EURASIP Journal on Applied Signal Processing
A distributed algorithm for managing multi-target identities in wireless ad-hoc sensor networks

IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Array processing for target DOA, localization, and classification based on AML and SVM algorithms in sensor networks

IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Mobility-Pattern based localization update algorithms for mobile wireless sensor networks

MSN'05 Proceedings of the First international conference on Mobile Ad-hoc and Sensor Networks
DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks

IEEE Transactions on Wireless Communications

Fault detection, correction, and tolerance for collaborative target localization in visual sensor networks

Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Detection of spatial events in CommonSens

Proceedings of the 2nd ACM international workshop on Events in multimedia
SeGrid: a secure grid infrastructure for sensor networks

MSN'05 Proceedings of the First international conference on Mobile Ad-hoc and Sensor Networks
Unidentifiable Attacks in Electric Power Systems

ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
EV-Loc: integrating electronic and visual signals for accurate localization

Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing
Collaborative localization in visual sensor networks

ACM Transactions on Sensor Networks (TOSN)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Fault-tolerant target detection and localization is a challenging task in collaborative sensor networks. This paper introduces our exploratory work toward identifying the targets in sensor networks with faulty sensors. We explore both spatial and temporal dimensions for data aggregation to decrease the false alarm rate and improve the target position accuracy. To filter out extreme measurements, the median of all readings in a close neighborhood of a sensor is used to approximate its local observation to the targets. The sensor whose observation is a local maxima computes a position estimate at each epoch. Results from multiple epoches are combined together to further decrease the false alarm rate and improve the target localization accuracy. Our algorithms have low computation and communication overheads. Simulation study demonstrates the validity and efficiency of our design.