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Employing PSO to Enhance RSS Range-Based Node Localization for Wireless Sensor Networks

並列摘要


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.

被引用紀錄


江奕均(2011)。感測網路中運用人工智慧演算法定位之成本與效能評估〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2011.00810

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