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AuthorAwad A.
AuthorHussein R.
AuthorMohamed A.
AuthorEl-Sherif A.A.
Available date2022-04-21T08:58:35Z
Publication Date2013
Publication NameProceedings - Conference on Local Computer Networks, LCN
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/LCN.2013.6761267
URIhttp://hdl.handle.net/10576/30165
AbstractBody Area Sensor Networks (BASNs) for healthcare applications have gained significant research interests recently due to the growing number of patients with chronic diseases requiring constant monitoring. Because of the limited power source and small form factors, BASNs have distinguished design and operational challenges, particularly focusing on energy optimization. In this paper, an Energy-Delay-Distortion cross-layer design that aims at minimizing the total energy consumption subject to data delay deadline and distortion threshold constraints is proposed. The optimal encoding and transmission energy are computed to minimize the total energy consumption in a delay constrained wireless body area sensor network. This cross-layer framework is proposed, across Application-MAC-Physical layers, under a constraint that all successfully received packets must have their delay smaller than their corresponding delay deadline and with maximum distortion less than the application distortion threshold. Due to the complexity of the optimal-proposed solution, sub-optimal solutions are also proposed. These solutions have close-to-optimal performance with lower complexity. In this context, there is complexity/energy-consumption trade-off, as shown in the simulation results. 2013 IEEE.
SponsorQatar National Research Fund
Languageen
PublisherIEEE Computer Society
SubjectConvex optimization
Energy utilization
Health care
Network layers
Sensor networks
BASNs
Body area sensor networks
Cross layer optimization
EEG signals
Health care application
Total energy consumption
Wireless body area sensor network
Wireless healthcares
Optimization
TitleEnergy-aware cross-layer optimization for EEG-based wireless monitoring applications
TypeConference Paper
Pagination356-363
dc.accessType Abstract Only


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