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Wireless sensor networks (WSNs) usually employ different ranging techniques to measure the distance between an unknown node and its neighboring anchor nodes, and based on the measured distance to estimate the location of the unknown node. In its operation, a range-based localization scheme uses trilateration or multilateration algorithms to obtain such range information. To trim down the hardware cost, some bring in iterative multilateration but encounter two problems (1) unable to localize unknown nodes with insufficient anchor nodes, and (2) the iterative process may build error accumulation. For improvement, this paper presents a new localization scheme, the key design of which is to improve localization success ratios by using the location data of remote anchors (provided by the closest neighbor nodes of an unknown node) to calculate the locations of unknown nodes with insufficient anchor nodes. The new scheme also employs the PSO algorithm to increase localization accuracy and the DV-distance approach to further boost up the success ratios of localization. Experimental evaluation shows that our new scheme performs constantly better than related target schemes either in increasing the localization success ratios or in decreasing location errors at reduced cost.

Keywords: wireless sensor networks, radio signal strength (RSS) ranging techniques, node localization schemes, particle swarm optimization (PSO), performance evaluation

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Received January 12, 2010; revised March 3, 2010; accepted June 1, 2010.
Communicated by Wanjiun Liao.
^* A preliminary version of this paper was presented at the 9th International Conference on Parallel and Distributed Computing, Applications and Technologies, Dunedin, New Zealand, Dec. 2008. The authors would like to thank Chih-Shin Lin and Yi-Jun Jiang for assisting with the revision of this work.