A Holistic Framework for Analyzing the Reliability of IoT Devices

Sammanfattning: In the rapidly evolving landscape of the Internet of Things (IoT), ensuring consistency and reliability becomes a top priority for a seamless user experience. In many instances, reliability is assessed through Quality of Service (QoS) metrics, sidelining traditional reliability metrics that thrive on time-dependent failure rates. The lack of a comprehensive framework that fully integrates all layers of an IoT system adds to the complexity. This gap makes it difficult to pinpoint specific areas that need improvement and to conduct a thorough assessment of the system’s reliability. This project addresses this intricate challenge, which holds significant relevance for industry professionals but remains unresolved. The project introduced an IoT architecture spanning the Power, Device, Edge, Application, and Cloud Layers. Within each layer, potential failure points were identified, and the reliability was analysed deploying time-based failure rates with an exponential distribution. Reliability Block Diagrams (RBDs) were employed to map the intricate inter-dependencies, though the framework’s adaptive nature allows for other system reliability methodologies. One of the primary outcomes of this research is the development of a new framework tailored for evaluating the reliability of various IoT system components. This framework yields insights into both system reliability and availability over time, serving as a pivotal tool for stakeholders such as device manufacturers, system integrators, network providers, and research institutions. The results show how the framework emerges as a pivotal starting point for IoT system reliability evaluation. Before this thesis, the feasibility of such a framework was uncertain, with concerns about its potential bias – being either too pessimistic or optimistic. Yet, the tangible results from this work affirm its capability to provide a balanced and reasonable reliability estimation, given the intricacies of IoT devices. This paves the way for subsequent research, enabling a deeper dive into targeted enhancements and fostering a nuanced understanding of IoT reliability.