Abstract
In sensor networks, the information is generated by sensors deployed in a geographic area, and sent to a node called ”sink” (or gateway). Since the node’s energy is battery limited, an efficient management of this resource affects the network’s lifetime. Our work presents a new approach called RPL (Repositioning, Prediction, Localization), that aims to extend the lifetime of the sensor network for a target tracking application. This is realized by switching sensors between active/sleep states and moving the sink close to the target’s future position. The movement of the sink reduces the energy needed for a packet transmission, and minimizes the number of hops between the sink and the emitting sensors. The proposed scheme is validated through simulations.
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Rahmé, J., Boukhatem, L., Al Agha, K. (2013). Predictive Sink Mobility for Target Tracking in Sensor Networks. In: Guyot, V. (eds) Advanced Infocomm Technology. ICAIT 2012. Lecture Notes in Computer Science, vol 7593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38227-7_31
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DOI: https://doi.org/10.1007/978-3-642-38227-7_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38226-0
Online ISBN: 978-3-642-38227-7
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