Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review

Abu Znaid, A.M.A. and Idris, M.Y.I. and Wahab, A.W.A. and Qabajeh, L.K. and Mahdi, O.A. (2017) Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review. Journal of Sensors, 2017. pp. 1-19. ISSN 1687-725X, DOI https://doi.org/10.1155/2017/1430145.

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Abstract

The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages and disadvantages. The similarities and differences of each scheme are investigated on the basis of significant parameters, namely, localization accuracy, computational cost, communication cost, and number of samples. We discuss the challenges and direction of the future research work for each parameter.

Item Type:	Article
Funders:	UMRG Grant RP036A-15AET
Uncontrolled Keywords:	Sequential Monte Carlo; Localization Methods; Mobile Wireless Sensor Networks
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Computer Science & Information Technology
Depositing User:	Ms. Juhaida Abd Rahim
Date Deposited:	10 Jul 2017 07:58
Last Modified:	10 Jul 2017 07:58
URI:	http://eprints.um.edu.my/id/eprint/17469

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