Performance Analysis of Blockchain of Things (BCoT) Systems for Enhancing Scalability and Efficiency

The Blockchain of Things (BCoT) ecosystem effectively tackles technological and business challenges across various domains. By utilising BCoT applications, issues related to decentralisation, data privacy, data protection, and network security are managed efficiently, enhancing operational reliability and scalability. However, recent BCoT implementations face performance issues, particularly in achieving efficient scalability, high throughput, and low latency. This research seeks to address these challenges, improve system performance, and ensure the scalability of the BCoT ecosystem.

The novel BCoT architecture showcases technological innovation by integrating a private Ethereum platform, IoT sensors, edge computing, and IPFS to create a secure, smart, and decentralised data storage system. Security within the architecture includes identity management, authentication, and access control for IoT devices, with each device assigned a unique identity. Secure communication is facilitated through MQTT and uTLS protocols, along with immutable access control rules.

The architecture's efficiency in handling large IoT data volumes was initially tested using the Random Forest classifier, which processes and prioritises sensor data in real time, achieving 99.53% accuracy in predicting conditions, assessing risk, and providing early warnings. Performance testing with the Geth Metrics tool demonstrated significant improvements over existing solutions, including a 45% reduction in latency, a 65% increase in throughput, and a 46% enhancement in Disk I/O performance. Additionally, CPU utilisation decreased by 33%, and memory usage during mining remained under 200 MB. Practical deployment and evaluation under realistic conditions showed the architecture's adaptability in executing up to 5000 transactions smoothly.

This research contributes to the field by introducing a scalable and secure BCoT architecture, adapting Blockchain mechanisms for IoT applications. The architecture's real-time, low-latency responses enhance its operational profile, offering opportunities for further research on current and future adaptations. It provides improved performance metrics, efficiency, and decision-making capabilities, impacting various practical applications. This work uniquely delivers a scalable and secure BCoT architecture, overcoming previous limitations.