ECO-FAST: An Energy Cognizant Fault-Tolerant Scheduler for Heterogeneous Computing Systems

Real-time embedded systems, fundamental to cyber-physical systems (CPS), employ microcontrollers, memory, and I/O devices to perform complex jobs within stringent time limits. A crucial component is the scheduler, which manages resources efficiently, ensuring timely job execution based on priority. Multiprocessor platforms, increasingly adopted in CPS, enhance performance, scalability, and fault tolerance by enabling parallel job execution and redundancy. Minimizing energy consumption is essential for extending battery life, especially in mobile CPS applications. However, most fault-tolerant strategies focus on either homogeneous multiprocessors or systems with only two processor types. This study introduces a heuristic scheduling technique, ECO-FAST, that addresses fault tolerance and energy management in systems with diverse processor types. Benchmark tests show that ECO-FAST outperforms a state-of-the-art approach by generating more secondary job copies to mitigate transient faults while significantly reducing energy consumption.