Prioritized payload tuning mechanism for wireless body area network-based healthcare systems

This paper presents a priority-based MAC-frame payload tuning mechanism with reduced energy consumption for healthcare systems that use Wireless Body Area Networks (WBANs). A fundamental problem in WBANs is to prioritize the physiological sensors depending on several health and external criteria. The challenge is to design a dynamic decision making model that can optimize the energy consumption of each physiological sensor. To address this problem we employ the concept of Fuzzy Inference System (FIS) in order to calculate Criticality Index (CI), which signifies the severity or the priority of the physiological data sensed by each sensor. Considering the obtained CI value we proceed with designing a Markov Decision Process (MDP) based dynamic decision making model in order to tune MAC-frame payload by optimizing the energy consumption of each sensor node. We achieve around 25% decrease in the overall energy consumption using our proposed mechanism.