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5. Introduction

Author

Abich, Geancarlo, Ost, Luciano, Reis, Ricardo, Abich, Geancarlo, Ost, Luciano, and Reis, Ricardo

Published
2023
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6. Related Works

Author

Abich, Geancarlo, Ost, Luciano, Reis, Ricardo, Abich, Geancarlo, Ost, Luciano, and Reis, Ricardo

Published
2023
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14. Introduction

Author

Rocha da Rosa, Felipe, Ost, Luciano, Reis, Ricardo, Rocha da Rosa, Felipe, Ost, Luciano, and Reis, Ricardo

Published
2020
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16. RAT: A Lightweight Architecture Independent System-Level Soft Error Mitigation Technique

Author

Gava, Jonas, Reis, Ricardo, Ost, Luciano, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Calimera, Andrea, editor, Gaillardon, Pierre-Emmanuel, editor, Korgaonkar, Kunal, editor, and Kvatinsky, Shahar, editor

Published
2021
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19. Efficient Soft Error Vulnerability Analysis Using Non-intrusive Fault Injection Techniques

Author

Bandeira, Vitor, Rosa, Felipe, Reis, Ricardo, Ost, Luciano, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Metzler, Carolina, editor, Gaillardon, Pierre-Emmanuel, editor, De Micheli, Giovanni, editor, and Silva-Cardenas, Carlos, editor

Published
2020
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20. Soft Error Assessment of Attitude Estimation Algorithms Running on Resource-Constrained Devices Under Neutron Radiation

Author

Gava, Jonas, Sartori, Tarso, Hanneman, Alex, Garibotti, Rafael, Moraes, Fernando, Calazans, Ney, Fourati, Hassen, Possamai Bastos, Rodrigo, Reis, Ricardo, and Ost, Luciano

Abstract

There is a growing incorporation of unmanned aerial vehicles (UAVs) within remote and urban environments due to their versatility and ability to access hard-to-reach and/or congested places. UAVs offer low-cost solutions for many applications, including healthcare (e.g., medical supplies delivery) and surveillance during public events, protests, or emergencies (e.g., a nuclear accident). However, drone utilization in urban areas often relies on strict regulations to ensure safe and responsible operation. UAVs are subject to radiation-induced soft errors, and identifying the most vulnerable software and hardware components to radiation exposure is an advisable task, which is difficult to undertake. An essential task to UAVs correct operation is attitude estimation (AE). This article assesses the soft error reliability of three AE algorithms running on two resource-constrained microprocessors under neutron radiation. Results suggest that the extended Kalman filter (EKF) algorithm provides the best Mean Work to Failure (MWTF) result for critical fault events, which is about $3\times $ more than the indirect Kalman filter (IKF) and $1.5\times $ more with respect to the novel quaternion Kalman filter (NQKF) algorithm.

Published
2024
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21. Assessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles

Author

Fleck, Marcos A., Pereira, Elisa G., Gava, Jonas F., Silva, Henrique B., Moraes, Fernando G., Calazans, Ney L.V., Meneguzzi, Felipe, Bastos, Rodrigo P., Reis, Ricardo A. L., Ost, Luciano, and Garibotti, Rafael

Abstract

The presence of unmanned surface vehicles (USVs) is increasingly frequent in lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the same environment and the risk of collisions with fixed structures and floating bodies, including other vessels. Therefore, the detection of obstacles and their reliable operation becomes primary in USVs. This work explores the effects caused by neutron radiation on an object detection algorithm tailored for USVs. Results report 77 silent data corruption (SDC)-induced failures, showing that radiation-induced soft errors contribute to missed and false detection of, respectively, existing and nonexistent objects. Furthermore, results suggest that object detection algorithms running with the multicore strategy ( $\text {FIT}_{\text {SDC}}$ rate of 34.3 at sea level and 308.6 at Lake Titicaca) exhibit a 16.4% greater resilience to SDCs compared to the single-core strategy.

Published
2024
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31. A Lightweight Mitigation Technique for Resource-constrained Devices Executing DNN Inference Models under Neutron Radiation

Author

Universidad de Alicante. Departamento de Tecnología Informática y Computación, Gava, Jonas, Hanneman, Alex, Abich, Geancarlo, Garibotti, Rafael, Cuenca-Asensi, Sergio, Bastos, Rodrigo Possamai, Reis, Ricardo, Ost, Luciano, Universidad de Alicante. Departamento de Tecnología Informática y Computación, Gava, Jonas, Hanneman, Alex, Abich, Geancarlo, Garibotti, Rafael, Cuenca-Asensi, Sergio, Bastos, Rodrigo Possamai, Reis, Ricardo, and Ost, Luciano

Abstract

Deep neural network (DNN) models are being deployed in safety-critical embedded devices for object identification, recognition, and even trajectory prediction. Optimised versions of such models, in particular the convolutional ones, are becoming increasingly common in resource-constrained edge-computing devices (e.g., sensors, drones), which typically rely on reduced memory footprint, low power budget and low-performance microprocessors. DNN models are prone to radiation-induced soft errors, and tackling their occurrence in resource-constrained devices is a mandatory and substantial challenge. While traditional replication-based soft error mitigation techniques will likely account for a reasonable performance penalty, hardware solutions are even more costly. To undertake this almost contradictory challenge, this work evaluates the efficiency of a lightweight software-based mitigation technique, called Register Allocation Technique (RAT), when applied to a convolutional neural network (CNN) model running on two commercial Arm microprocessors (i.e., Cortex-M4 and M7) under the effects of neutron radiation. Gathered results obtained from two neutron radiation campaigns suggest that RAT can reduce the number of critical faults in the CNN model running on both Arm Cortex-M microprocessors. Results also suggest that the SDC FIT rate of the RAT-hardened CNN model can be reduced in up to 83% with a runtime overhead of 32%.

Published
2023

32. Assessment of Radiation-Induced Soft Errors on Lightweight Cryptography Algorithms Running on a Resource-Constrained Device

Author

Universidad de Alicante. Departamento de Tecnología Informática y Computación, Gava, Jonas, Moura, Nicolas, Lucena, Joaquim, Rocha, Vinicius, Garibotti, Rafael, Calazans, Ney, Cuenca-Asensi, Sergio, Bastos, Rodrigo Possamai, Reis, Ricardo, Ost, Luciano, Universidad de Alicante. Departamento de Tecnología Informática y Computación, Gava, Jonas, Moura, Nicolas, Lucena, Joaquim, Rocha, Vinicius, Garibotti, Rafael, Calazans, Ney, Cuenca-Asensi, Sergio, Bastos, Rodrigo Possamai, Reis, Ricardo, and Ost, Luciano

Abstract

Most safety-critical edge-computing devices rely on lightweight cryptography (LWC) algorithms to provide security at minimum power and performance overhead. LWC algorithms are traditionally embedded as a hardware component, but with the advance of the Internet of Things (IoT), emerging firmware is more likely to support cryptography algorithms to comply with different security levels and industry-standards. This is the first work to present the soft error assessment of five cryptography algorithms executing in a low-power microprocessor running under neutron radiation, considering electronic code book (ECB) and counter (CTR) mode of operation implementations. Results obtained from two neutron radiation tests suggest that: ( i ) the NOEKEON algorithm gives the best relative soft error reliability, performance, power efficiency and memory footprint utilisation trade-offs between the five algorithms considering both ECB and CTR implementations, and ( ii ) cryptography solutions based on the counter mode of operation present better FIT rate for silent data corruption (SDC) and crash w.r.t. ECB implementations.

Published
2023

40. Early Soft Error Reliability Analysis on RISC-V

Author

Lodea, Nicolas, primary, Nunes, Willian, additional, Zanini, Vitor, additional, Sartori, Marcos, additional, Ost, Luciano, additional, Calazans, Ney, additional, Garibotti, Rafael, additional, and Marcon, Cesar, additional

Published
2022
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47. Assessment of Machine Learning Models in Computing System under Neutron Radiation

Author

Garay Trindade, Matheus, Sales Brum, Joao Paolo, Maldaner, Liége, Garibotti, Rafael, Ost, Luciano, Possamai Bastos, Rodrigo, Architectures and Methods for Resilient Systems (AMfoRS ), Techniques de l'Informatique et de la Microélectronique pour l'Architecture des systèmes intégrés (TIMA), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Universidade Federal de Santa Maria (UFSM), Pontifícia Universidade Católica do Rio Grande do Sul [Porto Alegre] (PUCRS), Loughborough University, and Universidade Federal de Santa Maria = Federal University of Santa Maria [Santa Maria, RS, Brazil] (UFSM)

Subjects
PACS 85.42, [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

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