Localization for Mobile Sensor Networks
Lingxuan Hu and David Evans
Tenth Annual International Conference on Mobile Computing and Networking
Philadelphia, 26 September - 1 October 2004
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
Complete Paper (13 pages)
MCL Project Page (includes
Physicrypt Group Page