An Energy Efficient Data Transmission in WSN Using Fuzzy‐Based Hybrid Philippine Eagle Tasmanian Devil Optimization

ABSTRACT In the realm of wireless sensor networks (WSNs), where energy efficiency and communication reliability are paramount, this paper proposes an innovative approach named Fuzzy‐based hybrid Philippine eagle optimization and Tasmanian devil optimization (FPEO‐TDO). WSNs utilize sensor nodes across diverse domains like agriculture, military, medicine, and manufacturing to gather data and monitor environments over prolonged periods. Efficient data transmission is crucial to conserve energy reserves in sensor nodes. The FPEO‐TDO model integrates the Philippine eagle optimization (PEO) and Tasmanian devil optimization (TDO) algorithms to optimize energy efficiency in WSNs. PEO and TDO algorithms are renowned for their abilities to enhance optimization processes by mimicking the behaviors of Philippine eagles and Tasmanian devils, respectively. By fusing these algorithms, our approach aims to minimize energy usage during data transfer, thereby extending network's lifetime and enhancing overall performance metrics. To determine optimal clusters within the network, a fuzzy logic model is employed, facilitating intelligent decision‐making for efficient data aggregation and transmission. Performance evaluation measures such as WSN lifetime, end‐to‐end delay, and network stability period are utilized to assess effectiveness of FPEO‐TDO. Experimental results demonstrate significant improvements, with a 98% of network lifetime and low energy consumption of 78 J compared with the traditional approaches, highlighting the efficacy of our proposed approach in enhancing WSN performance and energy efficiency.