Joint sensor placement and power rating selection in energy harvesting wireless sensor networks. Bushnaq, O. M., Al-Naffouri, T. Y., Chepuri, S. P., & Leus, G. In 2017 25th European Signal Processing Conference (EUSIPCO), pages 2423-2427, Aug, 2017.
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Paper doi abstract bibtex
Paper doi abstract bibtex In this paper, the focus is on optimal sensor placement and power rating selection for parameter estimation in wireless sensor networks (WSNs). We take into account the amount of energy harvested by the sensing nodes, communication link quality, and the observation accuracy at the sensor level. In particular, the aim is to reconstruct the estimation parameter with minimum error at a fusion center under a system budget constraint. To achieve this goal, a subset of sensing locations is selected from a large pool of candidate sensing locations. Furthermore, the type of sensor to be placed at those locations is selected from a given set of sensor types (e.g., sensors with different power ratings). We further investigate whether it is better to install a large number of cheap sensors, a few expensive sensors or a combination of different sensor types at the optimal locations.
@InProceedings{8081645,
author = {O. M. Bushnaq and T. Y. Al-Naffouri and S. P. Chepuri and G. Leus},
booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
title = {Joint sensor placement and power rating selection in energy harvesting wireless sensor networks},
year = {2017},
pages = {2423-2427},
abstract = {In this paper, the focus is on optimal sensor placement and power rating selection for parameter estimation in wireless sensor networks (WSNs). We take into account the amount of energy harvested by the sensing nodes, communication link quality, and the observation accuracy at the sensor level. In particular, the aim is to reconstruct the estimation parameter with minimum error at a fusion center under a system budget constraint. To achieve this goal, a subset of sensing locations is selected from a large pool of candidate sensing locations. Furthermore, the type of sensor to be placed at those locations is selected from a given set of sensor types (e.g., sensors with different power ratings). We further investigate whether it is better to install a large number of cheap sensors, a few expensive sensors or a combination of different sensor types at the optimal locations.},
keywords = {energy harvesting;parameter estimation;sensor placement;wireless sensor networks;joint sensor placement;power rating selection;energy harvesting wireless sensor networks;optimal sensor placement;parameter estimation;sensing nodes;communication link quality;sensor level;system budget constraint;optimal locations;Sensors;Batteries;Optimization;Covariance matrices;Europe;Signal processing;Wireless sensor networks;Wireless sensor networks;sensor selection;convex optimization;energy harvesting;estimation},
doi = {10.23919/EUSIPCO.2017.8081645},
issn = {2076-1465},
month = {Aug},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570347207.pdf},
}Downloads: 0
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