An integrated FSM-BABER-SROA framework for secure and energy-efficient internet of things networks using blockchain consensus

Abstract

The rapid expansion of the internet of things (IoT) and wireless sensor networks (WSNs) has intensified the demand for energy-efficient, reliable, and secure data transmission. Traditional clustering and static sleep scheduling approaches often fail to ensure long-term sustainability and tamper-resistant communication. This paper presents BABER-SROAChain, a hybrid optimization and security framework that integrates four core modules: i) Fuzzy similarity matrix (FSM)-based clustering for spatial-energy-aware node grouping, ii) Binary Al-Biruni earth radius (BABER) optimization for intelligent cluster head (CH) selection, iii) ship rescue optimization algorithm (SROA) for adaptive sleep scheduling, and iv) a lightweight blockchain protocol with modified practical byzantine fault tolerance (PBFT) consensus for secure inter-cluster communication. The unified objective function incorporates cluster efficiency, redundancy minimization, latency reduction, and packet delivery ratio maximization. Simulation experiments on large-scale WSNs (100–300 nodes) demonstrate that BABER-SROAChain achieves up to 20% improvement in network lifetime, 18% lower energy consumption, and 15% higher packet delivery ratio compared to state-of-the-art models. Additionally, it minimizes blockchain consensus latency while ensuring high data integrity. The proposed framework offers a scalable, secure, and energy-aware solution suitable for real-time IoT applications, including smart cities, healthcare monitoring, and industrial automation, while addressing the dual challenges of performance optimization and blockchain-based security.