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Quantifying the Resiliency of Fail-Operational Real-Time Networked Control Systems

Authors Arpan Gujarati, Mitra Nasri, Björn B. Brandenburg

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Author Details

Arpan Gujarati
  • Max Planck Institute for Software Systems (MPI-SWS), Kaiserslautern, Germany
Mitra Nasri
  • Max Planck Institute for Software Systems (MPI-SWS), Kaiserslautern, Germany
Björn B. Brandenburg
  • Max Planck Institute for Software Systems (MPI-SWS), Kaiserslautern, Germany

Funding

  • Nasri, Mitra: Mitra Nasri is supported by a post-doctoral fellowship awarded by the Alexander von Humboldt Foundation.

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Arpan Gujarati, Mitra Nasri, and Björn B. Brandenburg. Quantifying the Resiliency of Fail-Operational Real-Time Networked Control Systems. In 30th Euromicro Conference on Real-Time Systems (ECRTS 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 106, pp. 16:1-16:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.ECRTS.2018.16

Abstract

In time-sensitive, safety-critical systems that must be fail-operational, active replication is commonly used to mitigate transient faults that arise due to electromagnetic interference (EMI). However, designing an effective and well-performing active replication scheme is challenging since replication conflicts with the size, weight, power, and cost constraints of embedded applications. To enable a systematic and rigorous exploration of the resulting tradeoffs, we present an analysis to quantify the resiliency of fail-operational networked control systems against EMI-induced memory corruption, host crashes, and retransmission delays. Since control systems are typically robust to a few failed iterations, e.g., one missed actuation does not crash an inverted pendulum, traditional solutions based on hard real-time assumptions are often too pessimistic. Our analysis reduces this pessimism by modeling a control system's inherent robustness as an (m,k)-firm specification. A case study with an active suspension workload indicates that the analytical bounds closely predict the failure rate estimates obtained through simulation, thereby enabling a meaningful design-space exploration, and also demonstrates the utility of the analysis in identifying non-trivial and non-obvious reliability tradeoffs.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Embedded and cyber-physical systems
Keywords
  • probabilistic analysis
  • reliability analysis
  • networked control systems

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