Energy balancing for robotic aided clustered wireless sensor networks using mobility diversity algorithms

Licea, Daniel Bonilla, Nurellari, Edmond and Ghogho, Mounir (2018) Energy balancing for robotic aided clustered wireless sensor networks using mobility diversity algorithms. In: 26th European Signal Processing Conference (EUSIPCO 2018), 3rd-7th of September 2018, Rome, Italy.

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Energy balancing for robotic aided clustered wireless sensor networks using mobility diversity algorithms
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Item Type:Conference or Workshop contribution (Paper)
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Abstract

We consider the problem of energy balancing in a clustered wireless sensor network (WSN) deployed randomly in
a large field and aided by a mobile robot (MR). The sensor nodes (SNs) are tasked to monitor a region of interest (ROI) and report their test statistics to the cluster heads (CHs), which subsequently report to the fusion center (FC) over a wireless fading channel. To maximize the lifetime of the WSN, the MR is deployed to act as an adaptive relay between a subset of the CHs and the FC. To achieve this we develop a multiple−link mobility diversity algorithm (MDA) executed by the MR that will allow to compensate simultaneously for the small-scale fading at the established wireless links (i.e., the MR-to-FC as well as various CH-to-MR communication links). Simulation results show that the proposed MR aided technique is able to significantly reduce the transmission power required and thus extend the operational lifetime of the WSN. We also show how the effect of small-scale fading at various wireless links is mitigated by using the proposed multiple−link MDA executed by a MR equipped with a single antenna.

Keywords:Wireless sensor network, cluster, mobile robot, fading, mobility diversity
Subjects:H Engineering > H641 Telecommunications Engineering
H Engineering > H660 Control Systems
H Engineering > H600 Electronic and Electrical Engineering
H Engineering > H671 Robotics
Divisions:College of Science > School of Engineering
ID Code:32144
Deposited On:10 Jul 2018 13:40

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