A three-tier approach to Internet of Things softwarearchitecture design

Abstract

The Internet of Things (IoT) rapidly evolves, presenting both challenges and opportunities. This study emphasises the critical role of software in advancing IoT technologies, with a focus on machine learning (ML), fog computing, and process optimisation for security and resiliency. ML plays a pivotal role in IoT by predicting equipment failures, evaluating process efficiency, and enabling informed decision-making through real-time data analysis. By integrating ML models directly into IoT devices through edge computing, latency is reduced and data transmission requirements are minimised.

Fog computing and cloud computing address latency issues by moving computational resources closer to IoT devices, thereby enhancing scalability and optimising network resource usage. Security remains a paramount concern due to the growing number of connected devices and their inherent vulnerabilities. IoT software must balance efficiency, security, and performance by employing deep learning for anomaly detection, blockchain technologies for data transparency, and optimised encryption protocols.

The trend towards distributed architectures such as edge computing enhances system resilience by reducing latency and increasing fault tolerance. The proposed IoT system architecture follows a three-tier structure consisting of Edge, Fog, and Cloud levels. At the Edge level, initial data processing occurs directly on IoT devices, reducing latency and network load. The Fog level processes data within the local network, utilising more powerful computational resources for complex tasks while ensuring security through advanced machine learning techniques and encryption mechanisms. The Cloud level serves as a central repository for long-term data storage and global analysis, leveraging containerisation and orchestration technologies to ensure scalability and reliability.

This multi-layered architecture ensures efficient data processing, high security, and adaptability, making it suitable for real-time applications. The study highlights the importance of software in optimising data processing across these levels, thereby ensuring the IoT system’s resilience, scalability, and long-term sustainability.