The evolution of wireless technologies has enabled the creation of networks for several purposes as health care monitoring. The Wireless Body Area Networks (WBANs) enable continuous and real-time monitoring of physiological signals, but that monitoring leads to an excessive data transmission usage, and drastically affects the power consumption of the devices. Although there are approaches for reducing energy consumption, many of them do not consider information redundancy to reduce the power consumption. This paper proposes a hybrid approach of local data compression, called GROWN, to decrease information redundancy during data transmission and reduce the energy consumption. Our approach combines local data compression methods found in WSN. We have evaluated GROWN by experimentation, and the results show a decrease in energy consumption of the devices and an increase in network lifetime.
@article{arxiv.2010.09134,
title = {GROWN: Local Data Compression in Real-Time To Support Energy Efficiency in WBAN},
author = {Cainã Passos and Carlos Pedroso and Agnaldo Batista and Michele Nogueira and Aldri Santos},
journal= {arXiv preprint arXiv:2010.09134},
year = {2020}
}
Comments
This work has been accepted for presentation at IEEE LATINCOM 2020. 978-1-7281-8903-1/20/\$31.00 Copyright 2020 IEEE