Title :
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
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;
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
DOI :
10.1109/ECTICon.2012.6254261
