3,503 research outputs found
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An Empirical Study of the Effectiveness of 'Forcing Diversity' Based on a Large Population of Diverse Programs
Use of diverse software components is a viable defence against common-mode failures in redundant softwarebased systems. Various forms of "Diversity-Seeking Decisions" (“DSDs”) can be applied to the process of developing, or procuring, redundant components, to improve the chances of the resulting components not failing on the same demands. An open question is how effective these decisions, and their combinations, are for achieving large enough reliability gains. Using a large population of software programs, we studied experimentally the effectiveness of specific "DSDs" (and their combinations) mandating differences between redundant components. Some of these combinations produced much better improvements in system probability of failure per demand (PFD) than "uncontrolled" diversity did. Yet, our findings suggest that the gains from such "DSDs" vary significantly between them and between the application problems studied. The relationship between DSDs and system PFD is complex and does not allow for simple universal rules
(e.g. "the more diversity the better") to apply
A Survey of Fault-Tolerance Techniques for Embedded Systems from the Perspective of Power, Energy, and Thermal Issues
The relentless technology scaling has provided a significant increase in processor performance, but on the other hand, it has led to adverse impacts on system reliability. In particular, technology scaling increases the processor susceptibility to radiation-induced transient faults. Moreover, technology scaling with the discontinuation of Dennard scaling increases the power densities, thereby temperatures, on the chip. High temperature, in turn, accelerates transistor aging mechanisms, which may ultimately lead to permanent faults on the chip. To assure a reliable system operation, despite these potential reliability concerns, fault-tolerance techniques have emerged. Specifically, fault-tolerance techniques employ some kind of redundancies to satisfy specific reliability requirements. However, the integration of fault-tolerance techniques into real-time embedded systems complicates preserving timing constraints. As a remedy, many task mapping/scheduling policies have been proposed to consider the integration of fault-tolerance techniques and enforce both timing and reliability guarantees for real-time embedded systems. More advanced techniques aim additionally at minimizing power and energy while at the same time satisfying timing and reliability constraints. Recently, some scheduling techniques have started to tackle a new challenge, which is the temperature increase induced by employing fault-tolerance techniques. These emerging techniques aim at satisfying temperature constraints besides timing and reliability constraints. This paper provides an in-depth survey of the emerging research efforts that exploit fault-tolerance techniques while considering timing, power/energy, and temperature from the real-time embedded systems’ design perspective. In particular, the task mapping/scheduling policies for fault-tolerance real-time embedded systems are reviewed and classified according to their considered goals and constraints. Moreover, the employed fault-tolerance techniques, application models, and hardware models are considered as additional dimensions of the presented classification. Lastly, this survey gives deep insights into the main achievements and shortcomings of the existing approaches and highlights the most promising ones
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Computer trading and systemic risk: a nuclear perspective
Financial markets have evolved to become complex adaptive systems highly reliant on the communication speeds and processing power afforded by digital systems. Their failure could cause severe disruption to the provision of financial services and possibly the wider economy. In this study we consider whether a perspective from the nuclear industry can provide additional insights
An Automotive Case Study on the Limits of Approximation for Object Detection
The accuracy of camera-based object detection (CBOD) built upon deep learning
is often evaluated against the real objects in frames only. However, such
simplistic evaluation ignores the fact that many unimportant objects are small,
distant, or background, and hence, their misdetections have less impact than
those for closer, larger, and foreground objects in domains such as autonomous
driving. Moreover, sporadic misdetections are irrelevant since confidence on
detections is typically averaged across consecutive frames, and detection
devices (e.g. cameras, LiDARs) are often redundant, thus providing fault
tolerance.
This paper exploits such intrinsic fault tolerance of the CBOD process, and
assesses in an automotive case study to what extent CBOD can tolerate
approximation coming from multiple sources such as lower precision arithmetic,
approximate arithmetic units, and even random faults due to, for instance, low
voltage operation. We show that the accuracy impact of those sources of
approximation is within 1% of the baseline even when considering the three
approximate domains simultaneously, and hence, multiple sources of
approximation can be exploited to build highly efficient accelerators for CBOD
in cars
An overview of decision table literature 1982-1995.
This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.
MAFTIA Conceptual Model and Architecture
This document builds on the work reported in MAFTIA deliverable D1. It contains a refinement of the MAFTIA conceptual model and a discussion of the MAFTIA architecture. It also introduces the work done in WP6 on verification and assessment of security properties, which is reported on in more detail in MAFTIA deliverable D
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