Abstract:
The rapid advancements in wireless communication technologies and micro-electronics systems have fostered the development of small and intelligent micro-components that incorporate sensing devices and wireless communications into a single miniature circuit which is wearable or implantable inside the human body for medical and healthcare applications. These components when deployed over or across the body of subject communicate wirelessly to constitute Wireless Body Area Networks (WBANs). Since several WBAN nodes are sharing the wireless channel to report their collected data back to a base-station or sink node, the medium access mechanism must be robust, scalable, and energy efficient. Furthermore, it may also adapt to different data-rate requirements for different sensors in a heterogeneous WBAN.
In this research, Adaptive Sleep and Dynamic GTS allocation algorithms in WBAN have been implemented and compared with the proposed protocol entitled Adaptive Dynamic MAC that takes into consideration number and type of sensors, variable data-rates and energy requirements through managing sleep/wakeup intervals for WBAN nodes and implementing adaptive schedules for communication within the network. Network performance is compared on the basis of network lifetime, throughput and channel utilization through analytical model that is also verified in a customized simulator. Simulation results are gathered by observing network performance under variable network energy conditions, change in the position of gateway node, and effect of heterogeneous sensor nodes on mentioned performance parameters. It has been shown that Adaptive Dynamic MAC performs better than Dynamic GTS Allocation framework in all mentioned parameters. Furthermore, proposed algorithm has better network lifetime and throughput characteristics in comparison to baseline Adaptive Sleep algorithm.
