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

A Collaborative and Predictive Localization Algorithm for Wireless Sensor Networks


Abstract

Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with densely distributed sensor nodes. The non-localizable problem is prone to happening when a target moves into the WSN with sparsely distributed sensor nodes. To solve this problem, we propose a collaborative and predictive localization algorithm (CPLA). The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory. In addition, the collaborative and predictive schemes are designed to solve the non-localizable problems in the two-anchor nodes locating, one-anchor node locating and non-anchor node locating situations. Simulation results prove that the CPLA exhibits higher localization accuracy than other tested predictive localization algorithms either in the WSN with sparsely distributed sensor nodes or in the WSN with densely distributed sensor nodes.


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Cite this article

[IEEE Style]
Yuan Liu and Junjie Chen, "A Collaborative and Predictive Localization Algorithm for Wireless Sensor Networks," KSII Transactions on Internet and Information Systems, vol. 11, no. 7, pp. 3480-3500, 2017. DOI: 10.3837/tiis.2017.07.010

[ACM Style]
Liu, Y. and Chen, J. 2017. A Collaborative and Predictive Localization Algorithm for Wireless Sensor Networks. KSII Transactions on Internet and Information Systems, 11, 7, (2017), 3480-3500. DOI: 10.3837/tiis.2017.07.010