Minimizing energy of scalable distributed least squares localization

Diana Olivia, M. Ramakrishna, S. Divya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, Wireless Sensor Networks (WSN) have become a growing technology that has broad range of applications. One of the major areas of research in Sensor Networks is location estimation. Distributed Least Squares (DLS) algorithm is a good solution for fine grained localization. Here localization process is split into a complex precalculation and a simple postcalculation process. This paper presents a revised version of DLS, i.e. minimized energy Distributed Least Squares (meDLS) algorithm where each blind node collects position of neighbouring beacon nodes and directly sends it to the sink node for precalculation. The precaluated data is sent back to the blind node for postcalculation, where location of blind node is estimated. The proposed algorithm is simulated and compared with scalable DLS (sDLS) for computational and communicational cost.

Original languageEnglish
Title of host publicationEco-Friendly Computing and Communication Systems - International Conference, ICECCS 2012, Proceedings
Pages77-83
Number of pages7
DOIs
Publication statusPublished - 27-08-2012
EventInternational Conference on Eco-Friendly Computing and Communication Systems, ICECCS 2012 - Kochi, India
Duration: 09-08-201211-08-2012

Publication series

NameCommunications in Computer and Information Science
Volume305 CCIS
ISSN (Print)1865-0929

Conference

ConferenceInternational Conference on Eco-Friendly Computing and Communication Systems, ICECCS 2012
CountryIndia
CityKochi
Period09-08-1211-08-12

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

Olivia, D., Ramakrishna, M., & Divya, S. (2012). Minimizing energy of scalable distributed least squares localization. In Eco-Friendly Computing and Communication Systems - International Conference, ICECCS 2012, Proceedings (pp. 77-83). (Communications in Computer and Information Science; Vol. 305 CCIS). https://doi.org/10.1007/978-3-642-32112-2_10