Towards a Safe and Latency-Aware Fault-tolerant Scheduling Technique for Multi-rate Task Chains

In safety-critical real-time systems such as autonomous cars, fault-tolerance is essential for system reliability but can increase end-to-end latency and hinder schedulability. This paper presents a novel, safe, and latency-aware fault-tolerant scheduling technique for multi-rate task chains. A naive use of traditional fault-tolerance mechanisms, such as checkpointing and re-execution with recovery blocks, can violate end-to-end latency requirements. Our technique uses recovery blocks but leverages inherent task redundancies in multi-rate task chains (where data producers and consumers have different periods) to reduce the need for recovery. Moreover, it determines the priority of the recover blocks such that the end-to-end latency of the task chain is reduced in the presence of transient faults. Our experiments show that our technique significantly improves schedulability and reduces data age compared to the state-of-the-art checkpointing method. For instance, for systems with 4 to 16 cores and 10 to 40 tasks, we achieve up to 6 times higher schedulability and reduce data age by 21% under various fault levels.