Combined time and information redundancy for SEU-tolerance in energy-efficient real-time systems

Abstract

Abstract-Recently the trade-off between energy consumption and fault-tolerance in real-time systems has been highlighted. These works have focused on dynamic voltage scaling (DVS) to reduce dynamic energy dissipation and on time redundancy to achieve transient-fault tolerance. While the time redundancy technique exploits the available slack time to increase the faulttolerance by performing recovery executions, DVS exploits slack time to save energy. Therefore we believe there is a resource conflict between the time-redundancy technique and DVS. The first aim of this paper is to propose the usage of information redundancy to solve this problem. We demonstrate through analytical and experimental studies that it is possible to achieve both higher transient fault-tolerance (tolerance to single event upsets (SEU)) and less energy using a combination of information and time redundancy when compared with using time redundancy alone. The second aim of this paper is to analyze the interplay of transient-fault tolerance (SEU-tolerance) and adaptive body biasing (ABB) used to reduce static leakage energy, which has not been addressed in previous studies. We show that the same technique (i.e. the combination of time and information redundancy) is applicable to ABB-enabled systems and provides more advantages than time redundancy alone.

Low-Energy Standby-Sparing for Hard Real-Time Systems

“…In the related literature, various implementations of time-redundancy systems have been considered (e.g., [1][2] [3][5] [6]). These various implementations differ in energy management technique, recovery execution policy, and slack time management.…”

“…Note that, as discussed in Section II, here we focus only on transient faults. The occurrence of transient faults in digital systems usually follows a Poisson process [6][7] [29]. It has been observed that in DVS-enabled systems the rate of transient faults increases exponentially as the supply voltage decreases, so that the fault rate can be expressed as [32]: …”

“…To achieve the high reliability requirements of these systems, the use of hardware redundancy (also called hardware fault-tolerance [7] or replication [16]) is a must [16]. Indeed, in time-redundancy techniques, system reliability largely depends on the available amount of slack time so that when deadlines are tight, the reliability decreases significantly [6][7] [17]. In contrast, the use of hardware redundancy decouples the fault tolerance from the slack time and can provide high reliability even when deadlines are tight.…”

“…Furthermore, unlike our proposed technique, the technique of [30] cannot be used for dependent tasks. [6] has proposed to use a combination of information redundancy and time redundancy to address the resource conflict between timeredundancy and DVS on slack. However, this work has not considered hardware redundancy and does not provide any energy-management technique for fault-tolerant real-time systems.…”

Fault-tolerant average execution time optimization for general-purpose multi-processor system-on-chips

“…Al-Omari et al proposed a technique to handle a single error in multiprocessor systems while ensuring timing constraints, and Izosimov et al proposed for hard real-time safetycritical applications the optimization of re-execution and roll-back recovery under the assumption that errors are detected and that the maximal number of faults are known [8]. Ejlali et al explore the resource conflict between timeredundancy and dynamic voltage scaling [9] and Cai et al study fault-tolerant cache design [10].…”