An Energy-Efficient Data Forwarding Strategy for Heterogeneous WBANs

Monitoring human bodies and collecting physiological information are the major healthcare applications for wireless body area networks (WBANs). Due to the limited energy resource of body sensors, their energy depletions will cause severe network performance degradation, such as latency and energy efficiency. The heterogeneity of body sensors can result in different sensor energy consumption rates. Besides, the important degrees of monitored physiological data could vary hugely. Targeting at the above-mentioned problems, an energy-efficient data forwarding strategy (EDFS) is proposed in this paper to balance sensor energy consumption and improve network lifetime and collaborative operations of heterogeneous WBANs. Our major contributions include: 1) the original physiological data are processed by compressed sensing to reduce the data size to be transmitted and 2) the remaining energy levels, sampling frequency, and sensor importance are jointly considered by EDFS for the optimal relay sensor selection. With the EDFS, the energy-efficiency and reliability of WBAN data transmission can be improved. In addition, our simulation results demonstrate that the proposed EDFS can effectively deal with the frequently changing WBAN topologies while providing balanced energy consumption and energy efficiency.