Towards energy- and interference-aware health monitoring by using WBANs in medicine services

Abstract

We study the problems of energy consumption and interference for Wireless Body Area Networks (WBANs). Our model relies on a real medical monitoring, where the patient’s vital signals such as EEG, ECG, and EMG are regularly sampled at equal intervals to send to a medical center. For this purpose, an efficient scheme called Energy- and Interference-aware Routing and Scheduling (EIRS) is presented, which is based on three phases. EIRS first uses an energy-aware scheme to develop a data aggregation routing tree for each WBAN. In phase 2, it finds a set of appropriate channels for developed tree in terms of interference. Phase 3 employs a greedy algorithm to assign interfering transmissions to distinct time slots, while scheduling non-interfering transmissions at the same time slot. To realize energy efficient and reliable communication, EIRS jointly employs Euclidean distance, residual energy, channel diversity, multi-radio technology, and spatial reuse. As another advantage, the proposed scheme reduces inter-WBAN interference as well as intra-WBAN interference. Numerical results confirm the superiority of EIRS in terms of network lifetime, consumption of radio resources, interference, and delay.