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Localization algorithms for wireless sensor networks

University of British Columbia

Many applications in wireless sensor networks require sensor nodes to obtain their absolute or relative geographical positions. Due to the size, cost and energy restrictions imposed by sensor nodes, only a few nodes can be equipped with the Global Positioning System (GPS) capability and act as anchors for the rest of the network. The algorithms based on classical Multidimensional Scaling (MDS) [1][2] only require three or four anchor nodes and can provide higher accuracy than some other schemes. In the first part of this thesis, we propose and analyze the use of ordinal MDS for localization in wireless sensor networks. Ordinal MDS differs from classical MDS by that it only requires a monotonicity constraint between the shortest path distance and the Euclidean distance for each pair of nodes. Simulation studies are conducted under square and C-shaped topologies with different connectivity levels and number of anchors. Results show that ordinal MDS provides a lower position estimation error than classical MDS in both hop-based and range-based scenarios. In the second part of this thesis, we propose a concentric anchor-beacons (CAB) localization algorithm for wireless sensor networks. CAB is a range-free approach and uses a small number of anchor nodes. Each anchor emits several beacons at different power levels. From the information received by each beacon heard, nodes determine which annular ring they are located within each anchor. Each node uses the approximated center of intersection of the rings as its position estimate. Simulation results show that the estimation error reduces by half when anchors transmit beacons at two different power levels periodically instead of at a single level. CAB also gives a lower estimation error than other range-free localization schemes (e.g., Centroid, APIT) when the anchorto- node range ratio is less than four.

Text

2010-01-06

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http://hdl.handle.net/2429/17613

Electrical and Computer Engineering

University of British Columbia

UBCV

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