The slack time in real-time systems can be used by recovery schemes to increase system reliability as well as by frequency and voltage scaling techniques to save energy. Moreover, the rate of transient faults (i.e., soft errors caused, for example, by cosmic ray radiations) also depends on system operating frequency and supply voltage. Thus, there is an interesting trade-off between system reliability and energy consumption. This work first investigates the effects of frequency and voltage scaling on the fault rate and proposes two fault rate models based on previously published data. Then, the effects of energy management on reliability are studied. Our analysis results show that, energy management through frequency and voltage scaling could dramatically reduce system reliability, and ignoring the effects of energy management on the fault rate is too optimistic and may lead to unsatisfied system reliability.

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The effects of energy management on reliability in real-time embedded systems

Self-checking circuits can detect the presence of both transient and permanent faults. A self-checking circuit consists of a functional circuit that produces encoded output vectors and a checker that checks the output vectors. The checker has the ability to expose its own faults as well. The functional circuit can be either combinational or sequential. A self-checking system consists of an interconnection of self-checking circuits. The advantage of such a system is that errors can be caught as soon as they occur; thus, data contamination is prevented. Methods for the cost-effective design of combinational and sequential self-checking functional circuits and checkers are examined. The area overhead for all proposed design alternatives is studied in detail. >

Design and synthesis of self-checking VLSI circuits

Dynamic voltage and frequency scaling (DVFS) has been widely used to manage energy in real-time embedded systems. However, it was recently shown that DVFS has direct and adverse effects on system reliability. In this work, we investigate static and dynamic reliability-aware energy management schemes to minimize energy consumption for periodic real-time systems while preserving system reliability. Focusing on earliest deadline first (EDF) scheduling, we first show that the static version of the problem is NP-hard and propose two task-level utilization-based heuristics. Then, we develop a job-level online scheme by building on the idea of wrapper-tasks, to monitor and manage dynamic slack efficiently in reliability-aware settings. The feasibility of the dynamic scheme is formally proved. Finally, we present two integrated approaches to reclaim both static and dynamic slack at runtime. To preserve system reliability, the proposed schemes incorporate recovery tasks/jobs into the schedule as needed, while still using the remaining slack for energy savings. The proposed schemes are evaluated through extensive simulations. The results confirm that all the proposed schemes can preserve the system reliability, while the ordinary (but reliability-ignorant) energy management schemes result in drastically decreased system reliability. For the static heuristics, the energy savings are close to what can be achieved by an optimal solution by a margin of 5 percent. By effectively exploiting the runtime slack, the dynamic schemes can achieve additional energy savings while preserving system reliability.

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Reliability-Aware Energy Management for Periodic Real-Time Tasks

We describe how to exploit the scheduling slack in a real-time system to reduce energy consumption and achieve fault tolerance at the same time. During failure-free operation, a task takes checkpoints to enable recovery from failure. Additionally, the system exploits the slack to conserve energy by reducing the processor speed. If a task fails, it will restart from a saved checkpoint and execute at maximum speed to guarantee that the deadlines are met. We show that the number of checkpoints and their placements interact in subtle ways with the power management policy. We study two checkpoint placement policies for aperiodic tasks and analytically derive the optimal number of checkpoints to conserve energy under each. This optimal number allows the CPU speed to be slowed down to the level that yields minimum energy consumption, while still guaranteeing recoverability of tasks under each checkpointing policy. The results show that traditional periodic checkpointing is not the best policy for the combined purpose of conserving energy and guaranteeing recovery. Instead, better energy savings are possible through a nonuniform distribution of checkpoints that takes into account the energy consumption and reliability factors. Depending on the amount of slack and the checkpointing overhead, energy can be reduced by up to 68 percent under nonuniform checkpointing. We also demonstrate the applicability of these checkpoint placement policies to periodic tasks.

/pdf/the-interplay-of-power-management-and-fault-recovery-in-real-s26nj2zayq.pdf

The interplay of power management and fault recovery in real-time systems

Predictable performance in the event of failures is of paramount importance in most safety critical real-time systems. Various hardware as well as software fault-tolerant techniques are employed towards this goal among which checkpointing is a relatively cost-effective scheme. Since checkpointing schemes depend on time redundancy, they could affect the correctness of the system by causing deadlines to be missed. This paper provides exact schedulability tests for fault tolerant task sets under a specified failure hypothesis and employing checkpointing to assist in fault recovery. The effects of checkpointing strategies on task response time are analysed and some insights for optimal checkpointing are provided. The emphasis here is on utilizing this analysis as an off-line design support tool.

Analysis of Checkpointing for Real-Time Systems

In this paper a new modeling methodology to characterize failure processes in digital computers due to hardware transients is presented. The basic assumption made is that system sensitivity to hardware transient errors is a function of critical resources usage. The failure rate of a given resource is approximated by a deterministic function of time, depending on the average workload of that resource, plus a Gaussian process. The probability density function of the time to failure obtained under this assumption has a decreasing hazard function, explaining why decreasing hazard function densities such as the Weibull fit experimental data so well. Data on transient errors obtained from several systems are analyzed. Statistical tests confirm the good fit between decreasing hazard distributions and actual data. Finally, models of common fault-tolerant redundant structures are developed using decreasing hazard function distributions. The analysis indicates significant differences between reliability predictions based on the exponential distribution and those based on decreasing hazard function distributions. Reliability differences of 0.2 and factors greater than 2 in Mission Time Improvement are seen in model results. System designers should be aware of these differences.

McConnel

Papers

Derivation and Calibration of a Transient Error Reliability Model