Innovative Energy-Efficient Hierarchical Clustering Protocol for Wireless Body Area Networks Using the Firefly Algorithm

Wireless Body Area Networks (WBANs) play a vital role in medical applications and consist of Sensor nodes, however, face the challenge of rapidly depleting energy resources. Due to the difficulty of battery replacement, improving energy conservation is a key concern in the design of Wireless Body Area Networks (WBANs). This study proposes a novel clustering method that employs the Firefly Algorithm (FA) within WBAN networks to enhance energy efficiency. The research evaluates the effectiveness of the proposed approach through three scenarios. In the first scenario, sensor nodes are randomly deployed in the environment according to the IEEE 802.15.6 protocol, with one-dimensional placement and a 360-degree range in wireless sensor networks. The second scenario also involves random node distribution, but it incorporates the Firefly Algorithm (FA) for clustering, referred to as Firefly-Based Clustering (FBC). In the third scenario, the NODIC protocol is used for sensor node clustering, with cluster heads transmitting target information to the sink node. Simulation results using OPNET 11.5 show that the proposed method outperforms both the NODIC protocol and the IEEE 802.15.6 standard in terms of energy consumption and network lifespan.