OptiBC-WSN: Multi-Objective Optimization for Energy Efficiency, Security, and Scalability in IoT-Based Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are the core of Internet of Things (IoT) applications as they enable energy-efficient and scalable real-time data acquisition. However, WSN-based IoT systems have been facing great challenges in achieving energy efficiency, security and scalability especially in applications like smart agriculture. To tackle these problems, this study proposes a new framework called OptiBC-WSN that combines Particle Swarm Optimisation (PSO) clustering, AES-128 encryption, Proof of Authority (PoA) blockchain and Random Forest-based Intrusion Detection System (IDS). We have implemented PSO for energy efficient clustering, PoA for trust management and a Random Forest based IDS for attack detection on Intel Berkeley and GreenOrbs datasets. OptiBC-WSN consumes 0.25 mJ/node energy, LEACH consumes 5 mJ/node and K-Means+Bee consumes 0.3 mJ/node. It also achieves a breach rate of 0.13% vs. 2% for LEACH and 0.2% for K-Means+Bee and scales to 10,000 nodes with 15,950 bytes overhead (vs. 20,000 bytes for LEACH). Its IDS has 90% accuracy to DDoS, Sybil and Jamming attacks with fairness index 0.92. We perform scale-up tests from 100 to 10K nodes with GreenOrbs dataset and synthetic topology generation, and validate core energy and security metrics with the Intel Berkeley dataset (54 nodes). In smart agriculture it cuts irrigation by 15% and CO2 emissions by 60 kg/1,000 nodes/year. Future work will explore the use of blockchain sharding and adaptive IDS to improve the scalability and security of IoT.