This paper investigates an integrated approach for achieving fault tolerance and energy savings in real-time embedded systems. Fault tolerance is achieved via checkpointing, and energy is saved using dynamic voltage scaling (DVS). The authors present a feasibility analysis for checkpointing schemes for a constant processor speed as well as for variable processor speeds. DVS is then carried out on the basis of the feasibility analysis. The authors incorporate important practical issues such as faults during checkpointing, rollback recovery time, memory access time, and energy needed for checkpointing, as well as DVS and context switching overhead. Numerical results based on real-life checkpointing data and processor data sheets show that compared to fault-oblivious methods, the proposed approach significantly reduces power consumption and guarantees timely task completion in the presence of faults.

We investigate a unified approach for fault tolerance and dynamic power management in distributed real-time embedded systems. Coordinated checkpointing is used to achieve fault tolerance, and power management is carried out using dynamic voltage scaling. We present feasibility-of-scheduling tests for coordinated checkpointing schemes for a constant processor speed as well as for DVS-enabled processors that can operate at variable speeds. Simulation results based on the CORDS hardware/software co-synthesis system show that, compared to fault-oblivious methods, the proposed approach significantly reduces power consumption while guaranteeing timely task completion in the presence of faults.

We investigate dynamic voltage scaling (DVS) in real-time embedded systems that use checkpointing for fault tolerance. We present feasibility-of-scheduling tests for checkpointing schemes for a constant processor speed as well as for variable processor speeds. DVS is then carried out on the basis of the feasibility analysis. We incorporate practical issues such as faults during checkpointing and state restoration, rollback recovery time, memory access time and energy, and DVS overhead. Simulation results are presented for real-life checkpointing data and embedded processors.

Safety-critical embedded systems often operate in harsh environmental conditions that necessitate fault-tolerant computing techniques. In addition, many safety-critical systems execute real-time applications that require strict adherence to task deadlines. These embedded systems are also energy-constrained, since system lifetime is determined largely by the battery lifetime. In this paper, we investigate dynamic adaptation techniques based on checkpointing and dynamic voltage scaling (DVS) for fault tolerance and power management. We first present schedulability tests that provide the criteria under which checkpointing can provide fault tolerance and real-time guarantees. We then present an adaptive checkpointing scheme in which the checkpointing interval for a task is dynamically adjusted during execution, and checkpoints are inserted based not only on the available slack, but also on the occurrences of faults. Next, we combine adaptive checkpointing with DVS to achieve power reduction. Finally, we develop an adaptive checkpointing scheme for a set of multiple tasks in real-time systems. An offline preprocessing based on linear programming is used to determine the parameters that are provided as inputs to the online adaptive checkpointing procedure. Simulation results show that compared to previous methods, the proposed adaptive checkpointing approach increases the likelihood of timely task completion in the presence of faults. When combined with DVS, adaptive checkpointing also leads to considerable energy savings.