Ensemble modified firefly optimization-based fuzzy clustering protocol (MFOFCP) for IoT-assisted WSN

Effective communication in wireless sensor networks (WSNs) is a challenging task in light of their unique characteristics and wide range of usages in surveillance and observation. Clustering plays a essential role in conserving energy and improving the lifespan of WSN considering the limited energy capability of sensor nodes. To solve these issues, this study presents the Modified Firefly Optimization-based Fuzzy Clustering Protocol (MFOFCP). The modified firefly optimization algorithm optimizes fuzzy rules in MFOFCP, and a Mamdani fuzzy logic system selects cluster heads (CHs) relied on residual energy, inter-cluster distance, node degree, and speed. Utilizing an on-demand clustering technique to save computing costs and message traffic, the protocol creates energy-balanced clusters by taking member deviation, residual energy, and CH distance into account. Extensive simulations validate MFOFCP’s superior performance. It consistently produces fewer end-to-end delays, with an average improvement of 7% over KM-PSO and 6% over FLS-PSO. MFOFCP reduces packet loss from 13.7 to 27.7% and outperforms existing methods in congested networks by 3–8% in packet delivery ratio. Furthermore, compared to other protocols, MFOFCP improves energy conservation by 1% to 2.5%, prolonging network lifespan. According to these findings, MFOFCP is a viable option for enhancing WSNs’ energy efficiency, dependability, and communication efficiency.