Fault-Tolerance Strategies and Probabilistic Guarantees for Real-Time Systems

Ubiquitous deployment of embedded systems is having a substantial impact on our society, since they interact with our lives in many critical real-time applications. Typically, embedded systems used in safety or mission critical applications (e.g., aerospace, avionics, automotive or nuclear domains) work in harsh environments where they are exposed to frequent transient faults such as power supply jitter, network noise and radiation. They are also susceptible to errors originating from design and production faults. Hence, they have the design objective to maintain the properties of timeliness and functional correctness even under error occurrences. Fault-tolerance plays a crucial role towards achieving dependability, and the fundamental requirement for the design of effective and efficient fault-tolerance mechanisms is a realistic and applicable model of potential faults and their manifestations. An important factor to be considered in this context is the random nature of faults and errors, which, if addressed in the timing analysis by assuming a rigid worst-case occurrence scenario, may lead to inaccurate results. It is also important that the power, weight, space and cost constraints of embedded systems are addressed by efficiently using the available resources for fault-tolerance. This thesis presents a framework for designing predictably dependable embedded real-time systems by jointly addressing the timeliness and the reliability properties. It proposes a spectrum of fault-tolerance strategies particularly targeting embedded real-time systems. Efficient resource usage is attained by considering the diverse criticality levels of the systems' building blocks. The fault-tolerance strategies are complemented with the proposed probabilistic schedulability analysis techniques, which are based on a comprehensive stochastic fault and error model