Embedded real-time virtualized systems serve a wide range of functions for many important industries. They can encompass multiple independent applications sharing limited computational resources. Many models have been introduced to ensure reliability and energy efficiency for these systems. Hierarchical Real-Time Scheduling (HiRTS) is a framework to enable the sharing of resources. It is used alongside the Regularity-Based Resource Partition model (RRP) to achieve transparent scheduling. A checkpointing system is an effective method to resolve transient faults. However, checkpoint insertions are known to incur high time and energy overheads. This paper proposes a two-state regularity-based checkpointing model within the HiRTS framework. It will ensure fault tolerance when scheduling independent, mixedcriticality real-time task sets on limited resources. By reducing checkpoint insertions before the first fault, the system will achieve higher utilization and less overhead while still ensuring fault tolerance. The simulation-based experiments presented suggest the model could offer a significant increase in utilization and reliability. They will be used as a guideline for future simulations using more complex schedules.

Real-time embedded systems with safety-critical functions must often share a limited number of computational resources. Scheduling models within the Hierarchical Real-Time Scheduling (HiRTS) framework allow applications to share resources in an efficient manner. The Regularity-Based Resource Partition (RRP) model offers an efficient way to schedule resource partitions, ensuring transparent task scheduling. A model within this framework can manage resource distribution in real-time embedded systems, ensuring fault tolerance through a checkpointing system. However, checkpoint insertions are known to incur high time and energy overheads. This paper proposes the use of a Two-State checkpointing scheme in conjunction with the fault-tolerant hierarchical RRP model. By reducing the number of checkpoints during fault-free states, we can reduce time and energy overheads while still ensuring fault tolerance in worst-case fault scenarios. We outline our plan to construct a model that can offer low-overhead solution to transient faults in embedded real-time systems. We do so with the intent to build upon this model and eventually test it through simulation.