• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

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


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.


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Cite this article

[IEEE Style]
Wenlan Wu, Xianbin Wen, Haixia Xu, Liming Yuan and Qingxia Meng, "Accurate Range-free Localization Based on Quantum Particle Swarm Optimization in Heterogeneous Wireless Sensor Networks," KSII Transactions on Internet and Information Systems, vol. 12, no. 3, pp. 1083-1097, 2018. DOI: 10.3837/tiis.2018.03.006

[ACM Style]
Wu, W., Wen, X., Xu, H., Yuan, L., and Meng, Q. 2018. Accurate Range-free Localization Based on Quantum Particle Swarm Optimization in Heterogeneous Wireless Sensor Networks. KSII Transactions on Internet and Information Systems, 12, 3, (2018), 1083-1097. DOI: 10.3837/tiis.2018.03.006