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A Novel Greedy Optimization Localization Algorithm for Wireless Sensor Networks in a Concave Area
Wen Yingyou, Li Zhi, Meng Yinghui and Zhang Tongjie

Node localization plays an important role in many current and envisioned WSN applications. Most of existing algorithms are not applicable for networks in a concave area. To address this problem, a novel greedy optimization localization algorithm (GOLA) is proposed. The key of GOLA is the design of neighborhood function which only uses distances between neighbor nodes to generate a new set of estimated locations from an old one, two correction operations are used to alleviate the flip ambiguity. Furthermore, a method of initial solution generation is given. Both range-based and range-free localization can use GOLA to estimate locations of nodes if distances between neighbor nodes are measured by hardware or estimated by distance estimation algorithms. Simulation results indicate that GOLA can achieve more accurate and reliable localization results in a concave area.

Keywords: Localization; concave area; neighborhood function; flip ambiguity; wireless sensor network

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