Hardware certification for real-time safety-critical systems: State of the art

Kornecki, Andrew J.; Zalewski, Janusz

doi:10.1016/j.arcontrol.2009.12.003

Cited by 13 publications

(3 citation statements)

References 35 publications

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“…The validation process evaluates whether the developed system performs exactly as planned. For safety-critical systems, it is of paramount importance that the final product integrating both hardware and software is formally certified [120,121]. An overview of the design, verification and validation methods for medical devices can be found in [122][123][124].…”

Section: Brief Overview On Design Approachesmentioning

confidence: 99%

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

et al. 2016

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Significant increases in processing power, coupled with the miniaturization of processing units operating at low power levels, has motivated the embedding of modern control systems into medical devices. The design of such embedded decision-making strategies for medical applications is driven by multiple crucial factors, such as: (i) guaranteed safety in the presence of exogenous disturbances and unexpected system failures; (ii) constraints on computing resources; (iii) portability and longevity in terms of size and power consumption; and (iv) constraints on manufacturing and maintenance costs. Embedded control systems are especially compelling in the context of modern artificial pancreas systems (AP) used in glucose regulation for patients with type 1 diabetes mellitus (T1DM). Herein, a review of potential embedded control strategies that can be leveraged in a fully-automated and portable AP is presented. Amongst competing controllers, emphasis is provided on model predictive control (MPC), since it has been established as a very promising control strategy for glucose regulation using the AP. Challenges involved in the design, implementation and validation of safety-critical embedded model predictive controllers for the AP application are discussed in detail. Additionally, the computational expenditure inherent to MPC strategies is investigated, and a comparative study of runtime performances and storage requirements among modern quadratic programming solvers is reported for a desktop environment and a prototype hardware platform.

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Section: Brief Overview On Design Approachesmentioning

confidence: 99%

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

et al. 2016

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“…In analogue to existing practices in highly-demanding hardware-dependent areas [23,24], the certification procedure of the physical RNG should consists of at least the following four stages.…”

Section: Introductionmentioning

confidence: 99%

Independent quality assessment of a commercial quantum random number generator

Petrov

Radchenko

Steiger

et al. 2022

EPJ Quantum Technol.

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We reverse-engineer, test and analyse hardware and firmware of the commercial quantum-optical random number generator Quantis from ID Quantique. We show that $>99\%$ > 99 % of its output data originates in physically random processes: random timing of photon absorption in a semiconductor material, and random growth of avalanche owing to impact ionisation. Under a strong assumption that these processes correspond to a measurement of an initially pure state of the components, our analysis implies the unpredictability of the generated randomness. We have also found minor non-random contributions from imperfections in detector electronics and an internal processing algorithm, specific to this particular device. Our work shows that the design quality of a commercial quantum-optical randomness source can be verified without cooperation of the manufacturer and without access to the engineering documentation.

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“…For example, the European Cooperation for Space Standardization (ECSS) (responsible for standards mandatory for contractors working for ESA) published a set of requirements for FPGA development in space projects [3]. FPGAs have also widely been used in projects subject to the DO-254 aviation standard [4].…”

Section: Introductionmentioning

confidence: 99%

FIJI: Fault InJection Instrumenter

et al. 2019

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FPGAs are increasingly used in safety-critical applications (e.g., in aerospace and automotive engineering). Safety standards stipulate that implemented countermeasures against run-time faults such as detection and isolation of affected components, automatic reconfiguration, and redundancy mechanisms must be adequately verified. To that end, fault injection tests by various means have been established as a suitable method. For such tests, faults can be provoked by radiation, simulation, or manipulating the design, for example, by inserting additional logic or manipulating the synthesis flow. This work briefly summarizes the various fault injection approaches with a focus on methods that are capable of stressing critical nets of a design running on actual hardware without requiring to re-synthesize. While the state-of-the-art tools can work with complex designs, they often lack controllability of the exact timing of the injection events (which is important to track the system's response on faults in a logic simulation) and/or use a high amount of FPGA resources. To overcome these issues, we propose a resource-saving netlist-based fault injection framework Fault InJection Instrumenter (FIJI) that can target individual nets at test runtime. This paper presents FIJI's work flow, implementation details, and an evaluation in terms of FPGA resources, timing impact, and performance during instrumentation and test execution. The FIJI framework has been made publicly available by the authors under an open-source license.

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Hardware certification for real-time safety-critical systems: State of the art

Cited by 13 publications

References 35 publications

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

Independent quality assessment of a commercial quantum random number generator

FIJI: Fault InJection Instrumenter

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