Schedulability analysis for fault tolerant real-time systems

Predictability and fault tolerance are major requirements for complex real-time systems, which are either safety or mission critical. Traditionally fault tolerant techniques were employed to tackle the problem of ensuring correctness in the value domain only. We stress that the fault tolerance requirements and timing constraints are not orthogonal issues as they appear to be, and hence any viable approach must be an integrated one. Fault tolerance in a real-time system implies that the system is able to deliver correct results in a timely manner even in the presence of faults. Techniques employing time redundancy are commonly used for tolerating a wide class of faults such as transient faults. In these systems, it is essential that the exploitation of time redundancy for correctness does not jeopardize the timeliness attribute. Hence scheduling aspects of fault tolerant real-time systems become all the more important. The research work described in this thesis, focuses on the provision of tests for the feasibility analysis of fault tolerant task sets. These feasibility tests are based on fixed priority scheduling theory, and are formulated under various assumptions regarding frequency of fault occurrences and fault recovery strategy. We have analysed the effects of checkpointing schemes with respect to schedulability. Another important issue we addressed is the estimation of the system’s tolerance to perturbations in its timing parameters. Finally, we provide the notion of probabilistic guarantees to account for nondeterminisms. This complementary approach to the normal deterministic analysis of real-time systems, is an effort towards integrating scheduling theory and probabilistic fault models. The results presented in this thesis provide a foundation for employing fixed priority scheduling theory in the analysis of fault tolerant real-time systems. We expect these results will aid the system designers in the development of predictable and fault tolerant real-time systems.