Localization of Large‐Scale Wireless Sensor Networks Using Niching Particle Swarm Optimization and Reliable Anchor Selection

Abstract

Due to uneven deployment of anchor nodes in large-scale wireless sensor networks, localization performance is seriously affected by two problems. The first is that some unknown nodes lack enough noncollinear neighbouring anchors to localize themselves accurately. The second is that some unknown nodes have many neighbouring anchors to bring great computing burden during localization. This paper proposes a localization algorithm which combined niching particle swarm optimization and reliable reference node selection in order to solve these problems. For the first problem, the proposed algorithm selects the most reliable neighbouring localized nodes as the reference in localization and using niching idea to cope with localization ambiguity problem resulting from collinear anchors. For the second problem, the algorithm utilizes three criteria to choose a minimum set of reliable neighbouring anchors to localize an unknown node. Three criteria are given to choose reliable neighbouring anchors or localized nodes when localizing an unknown node, including distance, angle, and localization precision. The proposed algorithm has been compared with some existing range-based and distributed algorithms, and the results show that the proposed algorithm achieves higher localization accuracy with less time complexity than the current PSO-based localization algorithms and performs well for wireless sensor networks with coverage holes.

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“…as E E E is not, in general, a square matrix. Note that solving (5) has a complexity on the order of O(N 2 ) [30]. The performance of LinHPS has been compared with those of other algorithms, either geometric or from the soft computing domain.…”

A Modified Search and Rescue Optimization Based Node Localization Technique in WSN

“…To determine the enhancement, practical investigates are carried out in varied sizes of WSN ranging from 25-150 targeted nodes where the distance measurement are degraded by the Gaussian noise. Cui et al [17] proposed a localization method, which is combined with Niching PSO and trustworthy reference node chosen to resolve the problems. At the initial stage, the proposed method selects the stable neighboring localized nodes as a reference in the localization.…”