Fuzzy-MAC: An FIS based MAC protocol for a multi-constrained traffic in wireless body area networks

Abstract

In this paper, we introduce Fuzzy-MAC protocol to facilitate the uniform transmission of the multi-constrained data generated by the sensor devices in a wireless body area network (WBAN). A physiological sensor device allows us to monitor various health-related parameters. In the process, the sensed data become associated with diverse Quality of Service (QoS)-specific constraints depending on the application requirements, thus imposing a challenge in front of the enabling communication protocols such as IEEE 802.15.4. To deal with these multi-constrained traffic data, Fuzzy-MAC first categorizes the sensor data according to the application-specific QoS requirements. Moreover, improved channel access mechanisms are applied according to the priority class value assigned to the different data types. Lastly, employing a Fuzzy Inference System (FIS), Fuzzy-MAC brings context-awareness to a health monitoring environment. We conduct rigorous simulations of the proposed Fuzzy-MAC to justify the competence with the existing literature. The results show that the proposed MAC protocol outperforms the benchmarks in terms of throughput, average delay, and overall reliability of a WBAN.