Localization for Mobile Sensor Networks

Lingxuan Hu and David Evans
Tenth Annual International Conference on Mobile Computing and Networking (MobiCom 2004)
Philadelphia, 26 September - 1 October 2004

Abstract
Many sensor network applications require location awareness, but it is often too expensive to include a GPS receiver in a sensor network node. Hence, localization schemes for sensor networks typically use a small number of seed nodes that know their location and protocols whereby other nodes estimate their location from the messages they receive. Several such localization techniques have been proposed, but none of them consider mobile nodes and seeds. Although mobility would appear to make localization more difficult, in this paper we introduce the sequential Monte Carlo Localization method and argue that it can exploit mobility to improve the accuracy and precision of localization. Our approach does not require additional hardware on the nodes and works even when the movement of seeds and nodes is uncontrollable. We analyze the properties of our technique and report experimental results from simulations. Our scheme outperforms the best known static localization schemes under a wide range of conditions.

Keywords: Localization, sensor networks, mobility, Monte Carlo Localization.

Complete Paper (13 pages) [PDF]
Talk Slides [PPT]

MCL Project Page (includes simulator software)
Physicrypt Group Page


CS 655 David Evans - Publications
University of Virginia
Department of Computer Science
David Evans
evans@cs.virginia.edu