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ROCRSSI++: An Efficient Localization Algorithm for Wireless Sensor Networks

ROCRSSI++: An Efficient Localization Algorithm for Wireless Sensor Networks

Flavio Frattini, Christian Esposito, Stefano Russo
Copyright: © 2011 |Volume: 2 |Issue: 2 |Pages: 20
ISSN: 1947-9220|EISSN: 1947-9239|EISBN13: 9781613505328|DOI: 10.4018/jaras.2011040104
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MLA

Frattini, Flavio, et al. "ROCRSSI++: An Efficient Localization Algorithm for Wireless Sensor Networks." IJARAS vol.2, no.2 2011: pp.51-70. http://doi.org/10.4018/jaras.2011040104

APA

Frattini, F., Esposito, C., & Russo, S. (2011). ROCRSSI++: An Efficient Localization Algorithm for Wireless Sensor Networks. International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS), 2(2), 51-70. http://doi.org/10.4018/jaras.2011040104

Chicago

Frattini, Flavio, Christian Esposito, and Stefano Russo. "ROCRSSI++: An Efficient Localization Algorithm for Wireless Sensor Networks," International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS) 2, no.2: 51-70. http://doi.org/10.4018/jaras.2011040104

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Abstract

Localization within a Wireless Sensor Network consists of defining the position of a given set of sensors by satisfying some non-functional requirements such as (1) efficient energy consumption, (2) low communication or computation overhead, (3) no, or limited, use of particular hardware components, (4) fast localization, (5) robustness, and (6) low localization error. Although there are several algorithms and techniques available in literature, localization is viewed as an open issue because none of the current solutions are able to jointly satisfy all the previous requirements. An algorithm called ROCRSSI appears to be a suitable solution; however, it is affected by several inefficiencies that limit its effectiveness in real case scenarios. This paper proposes a refined version of this algorithm, called ROCRSSI++, which resolves such inefficiencies using and storing information gathered by the sensors in a more efficient manner. Several experiments on actual devices have been performed. The results show a reduction of the localization error with respect to the original algorithm. This paper investigates energy consumption and localization time required by the proposed approach.

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