Paper Info
Title
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.
Year
DOI
Venue
2018
10.1155/2018/2473875
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
Field
DocType
Volume
Particle swarm optimization,Software deployment,Computer science,Distributed algorithm,Time complexity,Wireless sensor network,Ambiguity,Distributed computing
Journal
2018
ISSN
Citations 
PageRank 
1530-8669
2
0.37
References 
Authors
25
4
Name
Order
Citations
PageRank
Huanqing Cui131.05
Yongquan Liang29121.60
Chuanai Zhou321.72
Ning Cao41821.45