Range-free localization approach for M2M communication system using mobile anchor nodes. (January 2015)

• Record Type: Journal Article
• Authors: Karim, Lutful; Nasser, N.; Mahmoud, Q.H.; Anpalagan, Alagan; Salti, T.E.
• Is Part Of: Journal of network and computer applications. Volume 47(2015)
• Page Start: 137
• Page End: 146
• Publication Date: 2015-01
• Subjects: M2M communications -- Wireless sensor networks -- Range-free -- Range-based -- Localization -- Mobile anchor node -- Trilateration -- Centroid; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2014.07.034
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Most existing range-free localization approaches use static anchor nodes. These approaches cannot be used for large scale Machine to Machine (M2M) communication networks since a fixed number of static anchor nodes cannot localize Machine Type Communication (MTC) devices such as sensors whenever more MTC devices are deployed in the network. Thus, this article introduces a Range-free, Energy efficient, Localization technique that uses Mobile Anchor (RELMA) nodes. This approach is scalable since the anchor nodes can move close to the newly deployed MTC devices in the network to localize them. The un-localized MTC devices receive beacon messages with the location information of mobile anchors whenever the anchors are within the sensing range of un-localized devices. Thus, RELMA is energy efficient and accurate because (i) the sensing range is much shorter than the communication range that other approaches use, and (ii) the intersected region of three sensing circles, where the un-localized device resides in, is very small. Simulation results show that RELMA outperforms existing Neighbor information Based Localization Scheme (NBLS) and Sink at the Origin Localization (SOL) approaches in terms of localization error and network energy consumption.