Jit fault detection: Increasing availability in 1oo2 systems just-in-time

Leo Botler, Nermin Kajtazovic, Konrad Diwold, Kay Römer

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

With silicon technology decreasing in size, memories get more susceptible to external influences, which can lead to soft errors. Although temporary, these errors constitute a challenge for safety-critical systems. Redundancy-based error detection is commonly used in industry to increase safety and mitigate these errors. When an error is detected, safety-critical systems are usually switched to a safe state. While this prevents failures, it negatively affects the system's availability. In this work, we propose Just-in-Time fault detection, a novel method which enables a system to be switched to the safe state only in case a detected error would affect the system's behavior. A software tool enabling the deployment of this method on an off-the-shelf processor is implemented, and the method is validated and compared with a state-of-the-art alternative approach using mixed-critical memories. Our results show an availability gain between 25.2% and 100% compared with the state-of-the-art approach while executing two different standard algorithms.

Originalspracheenglisch
TitelProceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020
Herausgeber (Verlag)Association of Computing Machinery
Seitenumfang10
ISBN (elektronisch)9781450388337
DOIs
PublikationsstatusVeröffentlicht - 25 Aug. 2020
Veranstaltung15th International Conference on Availability, Reliability and Security: ARES 2020 - Virtuell, Irland
Dauer: 25 Aug. 202028 Aug. 2020

Publikationsreihe

NameACM International Conference Proceeding Series

Konferenz

Konferenz15th International Conference on Availability, Reliability and Security
KurztitelARES 2020
Land/GebietIrland
OrtVirtuell
Zeitraum25/08/2028/08/20

ASJC Scopus subject areas

  • Human-computer interaction
  • Computernetzwerke und -kommunikation
  • Maschinelles Sehen und Mustererkennung
  • Software

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