Energy-Aware Dynamic Cluster Head Selection in WBANs using Fuzzy Logic

WBANs have become an essential technology for continuous healthcare monitoring by enabling real-time collection and transmission of physiological data such as heart rate, temperature, and electrocardiogram signals. In the long-term monitoring of WBAN sensor nodes, efficient energy management and reliable communication is one of great challenges, considering the limited battery resources of sensor nodes. A conventional clustering protocol like LEACH or E-LEACH typically chooses CHs without taking into account healthcare related parameters like energy, packet loss, and network lifetime, leading to unequal energy depletion, packet loss and shortened network lifetime. To overcome these drawbacks, a DCHS mechanism, which is based on fuzzy logic is proposed in this paper to select cluster head in an energy efficient manner for the healthcare monitoring application. The proposed approach aims to select the most appropriate CH for every communication round based on several decision criteria. The fuzzification process is used to deal with the uncertainty and to dynamically check the suitability of the nodes in the network under different network conditions. NS-3 simulations are used to evaluate the performance of the proposed model and its performance is compared with existing clustering approaches like LEACH and E-LEACH. The results of the simulation show that the proposed DCHS method achieves better network lifetime, low energy consumption, high PDR and low EED. The intelligent CH selection strategy also ensures that nodes that are likely to be overheated are not involved in intensive communication activities, so as to ensure patient safety and communication reliability. The presented approach is an adaptive and scalable routing approach suitable for the continuous and delay-critical healthcare monitoring applications.