Body sensors consume a significant amount of power when data is either transmitted or received. This paper evaluates the energy efficiency per utile bit as a function of the network load and data frame length while introducing power management solutions for a high-performance distributed queuing medium access control (DQ MAC) protocol in wireless body sensor networks. To do so, a new energy analytical model derived from delay theoretical studies is provided. Simulation results are displayed to further validate the protocol energy performance using IEEE 802.15.4 system parameters. The achieved outcome shows that the proposed scheme outperforms IEEEperformance using IEEE 802.15.4 system parameters. The achieved outcome shows that the proposed scheme outperforms IEEE 802.15.4 MAC in all possible scenarios.

Wireless body sensor networks (BSNs) in healthcare systems operate under conflicting requirements. These are the maintenance of the desired reliability and message latency of data transmissions, while simultaneously maximizing battery lifetime of individual body sensors. In doing so, the characteristics of the entire system, including physical, medium access control (MAC), and application layers have to be considered. The aim of this paper is to develop a new MAC model for BSNs to fulfill all these specific rigorous requirements under realistic medical settings. For that purpose, a novel cross-layer fuzzy-rule scheduling algorithm and energy-aware radio activation policies are introduced. The main idea is to integrate a fuzzy-logic system in each body sensor to deal with multiple cross-layer input variables of diverse nature in an independent manner. By being autonomously aware of their current condition, body sensors are able to demand a "collision-free" time slot, whenever they consider it strictly required (e.g. high system packet delay or low body sensor residual battery lifetime). Similarly, they may refuse to transmit, if there is a bad channel link, thus permitting another body sensor to do so. This results in improving the system overall performance. The proposed MAC model is evaluated by computer simulations in terms of quality of service and energy consumption under specific healthcare scenarios.

Significant power is consumed at a sensor node when it either transmits a packet or when it receives a packet. In this paper, we study energy efficiency as a function of the number of sensors in the network and the payload length. Additionally, we propose power management solutions based on a distributed queuing MAC protocol for wireless sensor networks. Analytical values for the energy consumption performance are derived as a function of the system parameters. The obtained results show that our proposed MAC scheme outperforms that of IEEE 802.15.4. These benefits are obtained from eliminating back-off periods and collisions in data packet transmissions while minimizing the control overhead and the overall energy consumption