Deterministic linear-hexagonal path traversal scheme for localization in wireless sensor networks
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Deterministic linear-hexagonal path traversal scheme for localization in wireless sensor networks Tisan Das1
•
Rakesh Ranjan Swain1,2 • Pabitra Mohan Khilar1 • Biswa Ranjan Senapati1
Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Recent trends of using wireless sensor network in various applications have reduced the significance of human intervention greatly. Due to the cost efficiency and energy constraint nature of wireless sensor network, mobile anchor nodes are preferred over the static ones for localization and thus reducing the amount of GPS modules required to be associated within sensor region. Use of mobile anchor node requires traversal path optimization so that average localization error as well the traversed path length is reduced. Specific localization algorithm is used in literature to measure average localization error, which results in different preference of traversal scheme. In order to encounter the problem and to make comparison among the traversal schemes more generalized, a novel evaluation metric namely Inverted Coverability, a variation of ANOVA, is proposed. Besides this, a novel traversing path scheme, Linear-Hexagonal (LH) traversal scheme is proposed. Mathematical analysis and the result shows better performance of the proposed scheme with respect to the total path traversed, number of beacon points, Inverted Coverability and average localization error over other geometric based deterministic path planning schemes like DOUBLE SCAN, CIRCLES, Z-curve, and Polygon approach. Keywords Localization GPS Anchor node Path planning Traversal scheme Wireless sensor network
1 Introduction Wireless sensor network, essentially consisting of wireless sensor nodes, are currently used in various applications— from military tactical border patrol monitoring to healthcare sector related applications, from environmental suspended particle monitoring to disastrous area aiding. A wireless sensor network consists of different types of & Tisan Das [email protected] Rakesh Ranjan Swain [email protected] Pabitra Mohan Khilar [email protected] Biswa Ranjan Senapati [email protected] 1
Department of Computer Science and Engineering, National Institute of Technology, Rourkela 769008, India
2
Present Address: School of Computer Science, National Institute of Science and Technology, Berhampur 761008, India
wireless sensor nodes capable of capturing different types of sensory information [1], because of which the sensor network is able to gather high dimensional data. In order to further process and obtain an overview, the captured data by sensor nodes are redirected to a processing device also known as the sink. Generally, wireless sensor networks are used in large scale and in situations where human intervention for monitoring is least expected [2], and hence in certain cases along with the gathered data, the location of captured data is also required. In those cases, the location of each and every indivi
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