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Tabu Search Algorithm for Localization in Wireless Sensor Network

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IJCA Proceedings on International Conference on Innovations in Computing Techniques (ICICT 2015)
© 2015 by IJCA Journal
ICICT 2015 - Number 1
Year of Publication: 2015
Authors:
Sivakumar. S
Lehanya. V

Sivakumar.s and Lehanya.v. Article: Tabu Search Algorithm for Localization in Wireless Sensor Network. IJCA Proceedings on International Conference on Innovations in Computing Techniques (ICICT 2015) ICICT 2015(1):10-14, July 2015. Full text available. BibTeX

@article{key:article,
	author = {Sivakumar.s and Lehanya.v},
	title = {Article: Tabu Search Algorithm for Localization in Wireless Sensor Network},
	journal = {IJCA Proceedings on International Conference on Innovations in Computing Techniques (ICICT 2015)},
	year = {2015},
	volume = {ICICT 2015},
	number = {1},
	pages = {10-14},
	month = {July},
	note = {Full text available}
}

Abstract

In Wireless Sensor Networks (WSNs), localization is considered as one of the most significant issue as it plays a critical role in many applications such as target tracking, routing etc. The main idea of localization in wireless sensor networks is that some deployed nodes with known coordinates (e. g. , GPS-equipped nodes) transmit beacons with their coordinates in order to help the other nodes in the sensing field to localize themselves. Broadly there are two types of localization methods used for calculating positions namely the range-based and range-free methods. The Mobile Anchor Positioning - Mobile Anchor & Neighbour (MAP-M&N) method categorized under the range-free technique is initially applied in which the sensor nodes use the location information of beacon packets of the mobile anchor node and the location packets of neighbouring nodes to improve the accuracy in localization of the sensor nodes. In this work, the proposed Meta-Heuristic Optimization Algorithm named Tabu Search is used along with MAP-M&N to further improve the accuracy in positioning of the sensor nodes. An analysis on Average localization error and comparison between these two approaches namely, MAP-M&N and MAP-M&N with Tabu Search have been done.

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