A hybrid range-free localization scheme in wireless sensor networks work in progress
Proceedings of the 2nd international conference on Scalable information systems
Considerations on quality metrics for self-localization algorithms
IWSOS'11 Proceedings of the 5th international conference on Self-organizing systems
Scalable localization in wireless sensor networks
HiPC'06 Proceedings of the 13th international conference on High Performance Computing
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
Splitting the linear least squares problem for precise localization in geosensor networks
GIScience'06 Proceedings of the 4th international conference on Geographic Information Science
ZigBee-based long-thin wireless sensor networks: address assignment and routing schemes
International Journal of Ad Hoc and Ubiquitous Computing
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For wireless sensor networks, localization is crucial due to the dynamic nature of deployment. In relative localization, nodes use the distance measurements to estimate their positions relative to some coordinate system. In absolute localization, a few nodes (called anchors) need to know their absolute positions, and all the other nodes are absolutely localized in the coordinate system of the anchors. Relative and absolute localization methods differ in both the performance and the cost. We present a new approach to relative localization that we refer to as: Simple Hybrid Absolute- Relative Positioning (SHARP). In SHARP, a relative localization method (M1) is used to relatively localize N_r reference nodes. Then, an absolute localization method (M2) uses these N_r nodes as anchors to localize the rest of the nodes. Choosing N_r, M1, and M2 gives a wide range of performance-cost tuning. We have done extensive simulation using the multidimensional scaling (MDS) method as M1 and the Ad-hoc Positioning System (APS) method as M2. While previous research shows that MDS gives better localization results than APS, our simulation shows that SHARP outperforms MDS if both the localization error and the cost are considered.