An efficient dynamic sampling method for energy harvesting body sensor node

Wireless Body Area Networks (WBANs) have received a lot of attention due to various medical and non-medical applications. However, the sensor energy remains a limitation for the lifetime of WBANs and eventually providing sustainable services. The highest amount of energy consumption is related to the sampling operation of the sensors. Therefore, reducing the sampling rate is the key solution to extend network lifetime. Though, existing sampling algorithms have two issues: (1) Existing methods increase energy consumption through unnecessary data sampling and (2) are a way of energy saving and cannot guarantee self-sustainability of sensors. Therefore, a Dynamic Sampling method based on Change Rate (DSCR) for energy-harvesting body nodes is proposed in this paper to address these two problems. Each node in DSCR is equipped with an adaptive energy manager. The node uses different methods for determining the sampling rate based on the energy level of sensor and the quality of energy harvesting in order to make the WBANs energy neutral. The energy manager in DSCR classifies the sensors into three classes A, B, and C in terms of the level of energy. The sampling rate of each class is determined independently. The simulations show that, compared to the state-the-art methods, the proposed method can reduce the sampling rate by 50.84% and data overhead by 78% on average while conserving data integrity.