The rapid growth of the Internet of Things (IoT) has led to increasingly complex and data-intensive systems, often with conflicting or interdependent application requirements. Many IoT applications have strict timing requirements, particularly for safety-critical services, e.g., in the industrial domain. However, due to the vastness of the IoT ecosystem, decisions about where, how, and what timing attributes to measure are often ad hoc and context-specific, fragmenting the community’s understanding of what “timing” entails. Moreover, security and privacy requirements are often overlooked within IoT. Common approaches to uphold confidentiality, integrity, and availability are often not suitable for resource-constrained IoT devices, as they may introduce unacceptable overhead. Consequently, designing a secure and time-critical IoT system is a challenging task.
These challenges motivate the goal of this licentiate thesis, which is to support timing and security in IoT systems through edge-centric approaches. To achieve this, the research follows an Action Design Research-inspired process and combines systematic literature reviews, surveys, and experimental evaluations using real IoT devices. The findings include a consolidated view of timing definitions, a cross-domain synthesis of explicitly reported timing-related requirements, and a unified categorization of timing metrics in the literature. In addition, comparative experiments of edge-centric data-reduction techniques highlight accuracy and reduction trade-offs for different applications, while a study of lightweight security mechanisms demonstrates how protocol choices and configuration influence timing behavior. Overall, this thesis contributes foundational knowledge for reasoning about timing and security in IoT systems by establishing key definitions, requirements, and metrics, and by evaluating selected technical mechanisms to meet these requirements.