GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust based consensus

Abstract

Blockchain technology, which has gained much attention from researchers, faces challenges when applied to resource-constrained devices in the Internet of Things (IoT). These challenges include significant network overhead and energy-intensive processes. We propose a trust-based ensemble consensus and Grey Wolf Optimization (GWO) algorithm to address these limitations. The trust-based ensemble consensus leverages Proof of Work (PoW) and Proof of Stake (PoS) consensus procedures to improve trust levels within the network. To boost scalability and throughput without sacrificing the security and privacy of IoT data, we utilize sidechaining with the efficient GWO algorithm, allowing the construction of parallel chains connected to the main blockchain. Our experimental results outperformed conventional models by increasing throughput by 12.5% while decreasing mining delay by 19.5% and energy usage by 18.3%. The conducted security analysis reveals the presented lightweight framework is robust against Finney, DoS, Sybil, and Masquerade attacks. These improvements suggest the potential of this approach to provide privacy, integrity, and anonymity in blockchain-enabled IoT systems for smart city applications.