ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Nath, Swaprava and Ekambaram, Venkatesan N and Kumar, Anurag and Kumar, Vijay P (2012) Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks. In: ACM TRANSACTIONS ON SENSOR NETWORKS, 8 (4).

[img] PDF
acm_tosn_8-4_a35-nath_2012.pdf - Published Version
Restricted to Registered users only

Download (4MB) | Request a copy
Official URL: http://dx.doi.org/10.1145/2240116.2240124

Abstract

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

Item Type: Journal Article
Publication: ACM TRANSACTIONS ON SENSOR NETWORKS
Publisher: ASSOC COMPUTING MACHINERY
Additional Information: Copyright for this article belongs to the ACM
Keywords: Theory; Algorithm; Performance; Random geometric graph; localization; belief propagation
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 23 Jan 2013 09:14
Last Modified: 23 Jan 2013 09:14
URI: http://eprints.iisc.ac.in/id/eprint/45280

Actions (login required)

View Item View Item