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AuthorAbdellatifA.A.
AuthorMohamedA.
AuthorChiasseriniC.-F.
Available date2019-10-03T10:50:03Z
Publication Date2018
Publication NameIEEE Systems Journal
ResourceScopus
ISSN19328184
URIhttp://dx.doi.org/10.1109/JSYST.2017.2785302
URIhttp://hdl.handle.net/10576/12035
AbstractThe increasing demand for intelligent and sustainable healthcare services has prompted the development of smart health systems. Rapid advances in wireless access technologies and in-network data reduction techniques can significantly assist in implementing such smart systems through providing seamless integration of heterogeneous wireless networks, medical devices, and ubiquitous access to data. Utilization of the spectrum across diverse radio technologies is expected to significantly enhance network capacity and quality of service (QoS) for emerging applications such as remote monitoring over mobile-health (m-health) systems. However, this imposes an essential need to develop innovative networks selection mechanisms that account for energy efficiency while meeting application quality requirements. In this context, this paper proposes an efficient networks selection mechanism with adaptive compression for improving medical data delivery over heterogeneous m-health systems. We consider different performance aspects, as well as networks characteristics and application requirements, so as to obtain an efficient solution that grasps the conflicting nature of the various users' objectives and addresses their inherent tradeoffs. The proposed methodology advocates a user-centric approach towards leveraging heterogeneous wireless networks to enhance the performance of m-health systems. Simulation results show that our solution significantly outperforms state-of-the-art techniques.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectHeterogeneouswirelessenvironment
mobilehealth
multi-RATarchitectures
networkselection
optimizationdecomposition
TitleUser-Centric Networks Selection with Adaptive Data Compression for Smart Health
TypeArticle
Pagination3618-3628
Issue Number4
Volume Number12
dc.accessType Abstract Only


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