An Adaptive Energy Optimization Mechanism for Decentralized Smart Healthcare Applications

Noman Zahid, Ali Hassan Sodhro, Mabrook S. Al-Rakhami, Lei Wang, Abdul Gumaei, Sandeep Pirbhulal

Forskningsoutput: Kapitel i bok/rapportKapitel i bokPeer review

6 Citeringar (Scopus)

Sammanfattning

Body Sensor Networks (BSNs) is the emerging driver to revolutionize the entire landscape of the medical field. However, sensor-based handheld devices suffer from high power drain and limited battery life, due to their resource-constrained nature. Hybridization of different energy control methods and protocol layers is a best approach to enhance the performance perimeters for smart and connected healthcare. Thus, this paper mainly contributes in two ways. First, adaptive duty-cycle optimization algorithm (ADO), is proposed which optimizes the active time by considering the specific power level which leads to more energy saving instead of increasing the sleep period unlike the traditional methods. Second, joint Green and sustainable healthcare framework is proposed. Extensive theoretical and experimental analysis is performed by adopting real-time data sets with Monte Carlo simulation in MATLAB, and it is revealed that proposed algorithm enhance reliability and energy saving by 24.43%, 36.54%, respectively. Thus it can be said that proposed algorithm have more potential for energy constrained sensor devices in smart and connected healthcare platform.

OriginalspråkEngelska
Titel på värdpublikation2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)
FörlagIEEE Conference Publishing
DOI
StatusPublicerad - 2021-juni-15
Externt publiceradJa
Evenemang93rd IEEE Vehicular Technology Conference, VTC 2021-Spring - Virtual, Online
Varaktighet: 2021-apr.-252021-apr.-28

Konferens

Konferens93rd IEEE Vehicular Technology Conference, VTC 2021-Spring
OrtVirtual, Online
Period21-04-2521-04-28

Nationell ämneskategori

  • Elektroteknik och elektronik (202)

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