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http://dx.doi.org/10.3837/tiis.2018.03.006

Accurate Range-free Localization Based on Quantum Particle Swarm Optimization in Heterogeneous Wireless Sensor Networks  

Wu, Wenlan (Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology)
Wen, Xianbin (Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology)
Xu, Haixia (Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology)
Yuan, Liming (Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology)
Meng, Qingxia (Tianjin University, School of Computer Science and Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.3, 2018 , pp. 1083-1097 More about this Journal
Abstract
This paper presents a novel range-free localization algorithm based on quantum particle swarm optimization. The proposed algorithm is capable of estimating the distance between two non-neighboring sensors for multi-hop heterogeneous wireless sensor networks where all nodes' communication ranges are different. Firstly, we construct a new cumulative distribution function of expected hop progress for sensor nodes with different transmission capability. Then, the distance between any two nodes can be computed accurately and effectively by deriving the mathematical expectation of cumulative distribution function. Finally, quantum particle swarm optimization algorithm is used to improve the positioning accuracy. Simulation results show that the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes for heterogeneous wireless sensor networks.
Keywords
Heterogeneous wireless sensor networks; range-free localization; multi-hop; expected hop progress; quantum particle swarm optimization;
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