Mid Sweden University

 Body Sensor Networks (BSNs) is the emergingdriver to revolutionize the entire landscape of the medicalfield. However, sensor-based handheld devices suffer fromhigh power drain and limited battery life, due to theirresource-constrained nature. Hybridization of differentenergy control methods and protocol layers is a best approachto enhance the performance perimeters for smart andconnected healthcare. Thus, this paper mainly contributes intwo ways. First, adaptive duty-cycle optimization algorithm(ADO), is proposed which optimizes the active time byconsidering the specific power level which leads to moreenergy saving instead of increasing the sleep period unlike thetraditional methods. Second, joint Green and sustainablehealthcare framework is proposed. Extensive theoretical andexperimental analysis is performed by adopting real-time datasets with Monte Carlo simulation in MATLAB, and it isrevealed that proposed algorithm enhance reliability andenergy saving by 24.43%, 36.54%, respectively. Thus it canbe said that proposed algorithm have more potential forenergy constrained sensor devices in smart and connectedhealthcare platform.