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Localization for Mobile Sensor Networks Based on MCL method using HW Prediction

G. Rajesh, Joe Winifred P. Rayen, J. Kamalesh, G. D. Karthik

Abstract


Awareness of the physical location for each node is required by many wireless sensor network applications. The location awareness is required by many sensor network applications, but it is often too expensive to include GPS receiver in a sensor network node. Therefore, Localization schemes make use of the Seed nodes that knows their location and protocols, thereby other nodes estimate their positions from the messages they received from it. The crux part is estimating the location of the mobile nodes and seeds keeping in mind all the constraints of the sensor nodes (energy, network, memory etc.,). Although mobility appears to make localization difficult, we adapt sequential Monte carlo Localization method along with minimum spanning tree concept to prove efficient localization. This approach does not need any extra hardware on the nodes and seeds even when the movement of seeds are uncontrollable.

Keywords


Localization, Wireless Sensor Networks, Mobility, Monte-Carlo Method, Minimum Spanning Tree, Holt-Winters Prediction, Robot Localization, Range Free Algorithms, Prediction Phase, Exponentially Weighted Moving Average.

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References


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