An optimum Markov random field-based localization algorithm wireless sensor networks

Author

Punviset, Rattikar ; Kasetkasem, Teerasit ; Kovavisaruch, La-or ; Isshiki, Tsuyoshi

Author_Institution

Dept. of Electr. Eng., Kasetsart Univ., Bangkok, Thailand

fYear

2012

fDate

16-18 May 2012

Firstpage

1

Lastpage

4

Abstract

The received signal strength (RSS) based localization algorithm is proposed in this paper. Here, the RSSs from neighboring sensors are assumed to be statistically dependent. The Markov random field model is employed to explain this dependency. From the model, the optimum sensor locations are obtained from the maximum likelihood estimate. Our experiment has shown that our proposed algorithm can improve the localization accuracy by 9.59% over the traditional localization algorithm without neighboring nodes´ information.

Keywords

Markov processes; maximum likelihood estimation; sensor placement; wireless sensor networks; RSS-based localization algorithm; localization accuracy; maximum likelihood estimation; optimum Markov random field-based localization algorithm; optimum sensor location; received signal strength; wireless sensor networks; Educational institutions; Maximum likelihood estimation; Receivers; Sensor phenomena and characterization; Signal processing algorithms; Wireless sensor networks; Expectation Maximization algorithm (EM); Markov Random Field (MRF); Maximum likelihood estimator(MLE); Wireless Sensor Network (WSN); localization;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2012 9th International Conference on

Conference_Location

Phetchaburi

Print_ISBN

978-1-4673-2026-9

Type

conf

DOI

10.1109/ECTICon.2012.6254261

Filename

6254261