7 Search Results for "Reghenzani, Federico"

Volume

OASIcs, Volume 98

Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)

NG-RES 2022, June 22, 2022, Budapest, Hungary

Editors: Marko Bertogna, Federico Terraneo, and Federico Reghenzani

Document
Complete Volume
DOI: 10.4230/OASIcs.NG-RES.2022
OASIcs, Volume 98, NG-RES 2022, Complete Volume

Authors: Marko Bertogna, Federico Terraneo, and Federico Reghenzani

Published in: OASIcs, Volume 98, Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)

Abstract
OASIcs, Volume 98, NG-RES 2022, Complete Volume
Cite as

Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022). Open Access Series in Informatics (OASIcs), Volume 98, pp. 1-58, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@Proceedings{bertogna_et_al:OASIcs.NG-RES.2022,
  title =	{{OASIcs, Volume 98, NG-RES 2022, Complete Volume}},
  booktitle =	{Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)},
  pages =	{1--58},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-221-1},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{98},
  editor =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2022},
  URN =		{urn:nbn:de:0030-drops-161070},
  doi =		{10.4230/OASIcs.NG-RES.2022},
  annote =	{Keywords: OASIcs, Volume 98, NG-RES 2022, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/OASIcs.NG-RES.2022.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Marko Bertogna, Federico Terraneo, and Federico Reghenzani

Published in: OASIcs, Volume 98, Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022). Open Access Series in Informatics (OASIcs), Volume 98, pp. 0:i-0:x, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{bertogna_et_al:OASIcs.NG-RES.2022.0,
  author =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)},
  pages =	{0:i--0:x},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-221-1},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{98},
  editor =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2022.0},
  URN =		{urn:nbn:de:0030-drops-161082},
  doi =		{10.4230/OASIcs.NG-RES.2022.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Paper
DOI: 10.4230/OASIcs.NG-RES.2022.1
Can We Trust AI-Powered Real-Time Embedded Systems? (Invited Paper)

Authors: Giorgio Buttazzo

Published in: OASIcs, Volume 98, Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)

Abstract
The excellent performance of deep neural networks and machine learning algorithms is pushing the industry to adopt such a technology in several application domains, including safety-critical ones, as self-driving vehicles, autonomous robots, and diagnosis support systems for medical applications. However, most of the AI methodologies available today have not been designed to work in safety-critical environments and several issues need to be solved, at different architecture levels, to make them trustworthy. This paper presents some of the major problems existing today in AI-powered embedded systems, highlighting possible solutions and research directions to support them, increasing their security, safety, and time predictability.
Cite as

Giorgio Buttazzo. Can We Trust AI-Powered Real-Time Embedded Systems? (Invited Paper). In Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022). Open Access Series in Informatics (OASIcs), Volume 98, pp. 1:1-1:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{buttazzo:OASIcs.NG-RES.2022.1,
  author =	{Buttazzo, Giorgio},
  title =	{{Can We Trust AI-Powered Real-Time Embedded Systems?}},
  booktitle =	{Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)},
  pages =	{1:1--1:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-221-1},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{98},
  editor =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2022.1},
  URN =		{urn:nbn:de:0030-drops-161099},
  doi =		{10.4230/OASIcs.NG-RES.2022.1},
  annote =	{Keywords: Real-Time Systems, Heterogeneous architectures, Trustworthy AI, Hypervisors, Deep learning, Adversarial attacks, FPGA acceleration, Mixed criticality systems}
}
Document
DOI: 10.4230/OASIcs.NG-RES.2022.2
Multi-Requirement Enforcement of Non-Functional Properties on MPSoCs Using Enforcement FSMs - A Case Study

Authors: Khalil Esper, Stefan Wildermann, and Jürgen Teich

Published in: OASIcs, Volume 98, Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)

Abstract
Embedded system applications usually have to meet real-time, energy or safety requirements on programs typically concurrently executed on a given MPSoC target platform. Enforcing such properties, e.g., by adapting the number of processors allocated to a program or by scaling the voltage/frequency mode of involved processors, is a difficult problem to solve, especially with a typically large varying environmental input (workload) per execution. In a previous work [Esper et al., 2021], we formalized the related enforcement problem using (a) finite state machines to model enforcement strategies, (b) discrete-time Markov chains to model the uncertain environment determining the system’s workload, and (c) the system response that defines the feedback for the reactive enforcer. In this paper, we apply that approach to specify and verify multi-requirement enforcement strategies and assess a case study for enforcing two independent requirements at the same time, i.e., latency and energy consumption. We evaluate and compare different enforcement strategies using probabilistic verification for the use case of an object detection application.
Cite as

Khalil Esper, Stefan Wildermann, and Jürgen Teich. Multi-Requirement Enforcement of Non-Functional Properties on MPSoCs Using Enforcement FSMs - A Case Study. In Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022). Open Access Series in Informatics (OASIcs), Volume 98, pp. 2:1-2:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{esper_et_al:OASIcs.NG-RES.2022.2,
  author =	{Esper, Khalil and Wildermann, Stefan and Teich, J\"{u}rgen},
  title =	{{Multi-Requirement Enforcement of Non-Functional Properties on MPSoCs Using Enforcement FSMs - A Case Study}},
  booktitle =	{Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)},
  pages =	{2:1--2:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-221-1},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{98},
  editor =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2022.2},
  URN =		{urn:nbn:de:0030-drops-161102},
  doi =		{10.4230/OASIcs.NG-RES.2022.2},
  annote =	{Keywords: Runtime Requirement Enforcement, Verification, Finite State Machine, Markov Chain, Energy Consumption, Probabilistic Model Cheking, PCTL, MPSoC}
}
Document
DOI: 10.4230/OASIcs.NG-RES.2022.3
Overlapping-Horizon MPC: A Novel Approach to Computational Constraints in Real-Time Predictive Control

Authors: Alberto Leva, Simone Formentin, and Silvano Seva

Published in: OASIcs, Volume 98, Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)

Abstract
Model predictive control (MPC) represents the state of the art technology for multivariable systems subject to hard signal constraints. Nonetheless, in many real-time applications MPC cannot be employed as the minimum acceptable sampling frequency is not compatible with the computational limits of the available hardware, i.e., the optimisation task cannot be accomplished in one sampling period. In this paper we generalise the classical receding-horizon MPC rationale to the case where n > 1 sampling intervals are required to compute the control trajectory. We call our scheme Overlapping-horizon MPC - OH-MPC for short - and we numerically show its attitude at providing a tunable trade-off between optimisation quality and real-time capabilities.
Cite as

Alberto Leva, Simone Formentin, and Silvano Seva. Overlapping-Horizon MPC: A Novel Approach to Computational Constraints in Real-Time Predictive Control. In Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022). Open Access Series in Informatics (OASIcs), Volume 98, pp. 3:1-3:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{leva_et_al:OASIcs.NG-RES.2022.3,
  author =	{Leva, Alberto and Formentin, Simone and Seva, Silvano},
  title =	{{Overlapping-Horizon MPC: A Novel Approach to Computational Constraints in Real-Time Predictive Control}},
  booktitle =	{Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)},
  pages =	{3:1--3:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-221-1},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{98},
  editor =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2022.3},
  URN =		{urn:nbn:de:0030-drops-161118},
  doi =		{10.4230/OASIcs.NG-RES.2022.3},
  annote =	{Keywords: real-time control, model predictive control}
}
Document
DOI: 10.4230/OASIcs.NG-RES.2022.4
Ahead-Of-Real-Time (ART): A Methodology for Static Reduction of Worst-Case Execution Time

Authors: Daniele Cattaneo, Gabriele Magnani, Stefano Cherubin, and Giovanni Agosta

Published in: OASIcs, Volume 98, Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)

Abstract
Precision tuning is an approximate computing technique for trading precision with lower execution time, and it has been increasingly important in embedded and high-performance computing applications. In particular, embedded applications benefit from lower precision in order to reduce or remove the dependency on computationally-expensive data types such as floating point. Amongst such applications, an important fraction are mission-critical tasks, such as control systems for vehicles or medical use-cases. In this context, the usefulness of precision tuning is limited by concerns about verificability of real-time and quality-of-service constraints. However, with the introduction of optimisations techniques based on integer linear programming and rigorous WCET (Worst-Case Execution Time) models, these constraints not only can be verified automatically, but it becomes possible to use precision tuning to automatically enforce these constraints even when not previously possible. In this work, we show how to combine precision tuning with WCET analysis to enforce a limit on the execution time by using a constraint-based code optimisation pass with a state-of-the-art precision tuning framework.
Cite as

Daniele Cattaneo, Gabriele Magnani, Stefano Cherubin, and Giovanni Agosta. Ahead-Of-Real-Time (ART): A Methodology for Static Reduction of Worst-Case Execution Time. In Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022). Open Access Series in Informatics (OASIcs), Volume 98, pp. 4:1-4:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{cattaneo_et_al:OASIcs.NG-RES.2022.4,
  author =	{Cattaneo, Daniele and Magnani, Gabriele and Cherubin, Stefano and Agosta, Giovanni},
  title =	{{Ahead-Of-Real-Time (ART): A Methodology for Static Reduction of Worst-Case Execution Time}},
  booktitle =	{Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)},
  pages =	{4:1--4:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-221-1},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{98},
  editor =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2022.4},
  URN =		{urn:nbn:de:0030-drops-161120},
  doi =		{10.4230/OASIcs.NG-RES.2022.4},
  annote =	{Keywords: Approximate Computing, Precision Tuning, Worst-Case Execution Time}
}
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