MDS-Based Localization

MDS-Based Localization

Ahmed A. Ahmed, Xiaoli Li, Yi Shang, Hongchi Shi
DOI: 10.4018/978-1-60566-396-8.ch008
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Abstract

The authors present several network node localization methods that are based on multidimensional scaling (MDS) techniques. Four algorithms are introduced: MDS-MAP(C), MDS-MAP(P), MDS-Hybrid, and RangeQ-MDS. MDS-MAP(C) is a centralized algorithm that simply applies MDS to estimate node positions. In MDS-MAP(P), a local map is built at each node of the immediate vicinity, then these maps are merged together to form a global map. MDS-Hybrid uses MDS-MAP(C) to relatively localize Nr reference nodes. Then, an absolute localization method uses these Nr nodes as anchors to localize the rest of the network. Finally, RangeQ-MDS assumes the absence of an RSSI-distance mapping function. It uses a quantized RSSI-based distance estimation technique (called RangeQ) to achieve more precise hop distances than other range-free approaches do. While MDS-MAP(C), MDS-MAP(P), and MDSHybrid can be range-aware or range-free, RangeQ-MDS is partially range-aware.
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Problem Formulation

The network is represented as a connected undirected graph G = (V, E), where V is the set of sensor nodes, of which there exist A978-1-60566-396-8.ch008.m01V special nodes (called anchors) with known positions, and E is the set of edges connecting neighboring nodes. For the range-free case, the edges in the graph correspond to the connectivity information. For the range-aware case, the edges are associated with values corresponding to the estimated distances.

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