Title :
Sensor Network Localization for Moving Sensors
Author :
Agarwal, Abhishek ; Daume, Hal ; Phillips, Jeff M. ; Venkatasubramanian, Suresh
Author_Institution :
Univ. of Maryland, College Park, MD, USA
Abstract :
Sensor network localization (SNL) is the problem of determining the locations of the sensors given sparse and usually noisy inter-communication distances among them. In this work we propose an iterative algorithm named PLACEMENT to solve the SNL problem. This iterative algorithm requires an initial estimation of the locations and in each iteration, is guaranteed to reduce the cost function. The proposed algorithm is able to take advantage of the good initial estimation of sensor locations making it suitable for localizing moving sensors, and also suitable for the refinement of the results produced by other algorithms. Our algorithm is very scalable. We have experimented with a variety of sensor networks and have shown that the proposed algorithm outperforms existing algorithms both in terms of speed and accuracy in almost all experiments. Our algorithm can embed 120,000 sensors in less than 20 minutes.
Keywords :
iterative methods; wireless sensor networks; PLACEMENT; SNL problem; cost function reduction; iterative algorithm; moving sensors; noisy intercommunication distance; sensor network localization; Cost function; Distance measurement; Educational institutions; Global Positioning System; Noise; Noise measurement; Wireless sensor networks; Embedding; sensor network localization;
Conference_Titel :
Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4673-5164-5
DOI :
10.1109/ICDMW.2012.123