Energy-Aware Fault-Tolerant Mapping of Mixed-Criticality Tasks on Heterogeneous Multicores

Due to the different timing requirements of tasks in different criticality modes, it is challenging for Mixed-Criticality Systems (MCSs) designers to use time-redundant fault-tolerant techniques. Checkpointing with rollback recovery can be an effective option for ensuring the reliability of tasks in such systems. Despite the benefits of checkpointing it can impose significant energy overheads. A common approach to overcome this energy consumption is using Dynamic Voltage and Frequency Scaling (DVFS). However, DVFS can lead to missed deadlines for high-criticality tasks. In addition, there is an increasing trend of deploying tasks on heterogeneous multicore platforms. These platforms offer promising opportunities to meet the design requirements of mixed-criticality applications more effectively. In this paper, we propose an energy-aware checkpointing scheme for mixed-criticality tasks on heterogeneous multicore platforms. First, we calculate the timing demand of each task according to DVFS and the time overhead of checkpointing to perform the EY schedulability test in different operational modes of the system. Then we focus on energy-aware mapping of tasks to heterogeneous platforms. Finally, we use DVFS to mitigate the energy overhead of checkpoints. Our experiments show that our scheme can improve schedulability by an average of 16% compared to Little Island First (LIF) mapping, while the energy does not change appreciably. Moreover, it consumes up to 36% (20% on average) less energy compared to Big Island First (BLF) mapping.