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187 results on '"Cucu-Grosjean, Liliana"'

1. A Survey of Probabilistic Timing Analysis Techniques for Real-Time Systems

Author

Davis, Robert I. and Cucu-Grosjean, Liliana

Subjects
probabilistic, real-time, timing analysis, Technology, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Electronics, TK7800-8360
Abstract

This survey covers probabilistic timing analysis techniques for real-time systems. It reviews and critiques the key results in the field from its origins in 2000 to the latest research published up to the end of August 2018. The survey provides a taxonomy of the different methods used, and a classification of existing research. A detailed review is provided covering the main subject areas: static probabilistic timing analysis, measurement-based probabilistic timing analysis, and hybrid methods. In addition, research on supporting mechanisms and techniques, case studies, and evaluations is also reviewed. The survey concludes by identifying open issues, key challenges and possible directions for future research.

Published
2019
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2. A Survey of Probabilistic Schedulability Analysis Techniques for Real-Time Systems

Author

Davis, Robert I. and Cucu-Grosjean, Liliana

Subjects
probabilistic, real-time, schedulability analysis, scheduling, Technology, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Electronics, TK7800-8360
Abstract

This survey covers schedulability analysis techniques for probabilistic real-time systems. It reviews the key results in the field from its origins in the late 1980s to the latest research published up to the end of August 2018. The survey outlinesfundamental concepts and highlights key issues. It provides a taxonomy of the different methods used, and a classification of existing research. A detailed review is provided covering the main subject areas as well as research on supporting techniques. The survey concludes by identifying open issues, key challenges and possible directions for future research.

Published
2019
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4. Response Times Parametric Estimation of Real-Time Systems

Author

Zagalo, Kevin, Verbytska, Olena, Cucu-Grosjean, Liliana, and Bar-Hen, Avner

Subjects
Electrical Engineering and Systems Science - Systems and Control, Mathematics - Statistics Theory
Abstract

Real-time systems are a set of programs, a scheduling policy and a system architecture, constrained by timing requirements. Most of daily embedded devices are real-time systems, e.g. airplanes, cars, trains, spatial probes, etc. The time required by a program for its end-to-end execution is called its response time. Usually, upper-bounds of response times are computed in order to provide safe deadline miss probabilities. In this paper, we propose a suited re-parametrization of the inverse Gaussian mixture distribution adapted to response times of real-time systems and the estimation of deadline miss probabilities. The parameters and their associated deadline miss probabilities are estimated with an adapted Expectation-Maximization algorithm., Comment: 21 pages, 6 figures, 2 tables

Published
2022

8. Invited Paper: Statistical, Stochastic or Probabilistic (Worst-Case Execution) Execution Time? - What Impact on the Multicore Composability

Author

Liliana Cucu-Grosjean, Cucu-Grosjean, Liliana, Liliana Cucu-Grosjean, and Cucu-Grosjean, Liliana

Abstract

The problem of estimating worst-case execution times of programs on processors has appeared within the context of critical industries like avionics or space. Rapidly adopted by the real-time scheduling community, worst-case execution time estimates of programs or tasks are mandatory to understand the time behaviour of a real-time system. Analyzing such time behaviour is done, often, with an important pessimism due to the consideration of worst-case scenarios. A decreased pessimism has been obtained by understanding that large execution times of a program have low probability of appearance. Probabilistic (worst-case) execution time notion has been proposed. Nevertheless, independence hypotheses makes difficult today to calculate the probabilistic worst-case execution time of a program and current approaches are built, often, on statistical estimators based on the use of Extreme Value Theory or concentration inequalities. Thus, future probabilistic time analyses are expected to consider worst-case execution times estimates obtained by using statistical estimators on measured execution times instead of probabilistic (worst-case) execution times estimations. Within this paper, we discuss the opportunity of differentiating probabilistic (worst-case) execution times from statistical (worst-case) execution times and how dependence between execution times are better or easier captured by each of the definition, while stochastic execution times could be, also, an appropriate alternative.

Published
2024
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9. On the periodic behavior of real-time schedulers on identical multiprocessor platforms

Author

Grolleau, Emmanuel, Goossens, Joël, and Cucu-Grosjean, Liliana

Subjects
Computer Science - Operating Systems
Abstract

This paper is proposing a general periodicity result concerning any deterministic and memoryless scheduling algorithm (including non-work-conserving algorithms), for any context, on identical multiprocessor platforms. By context we mean the hardware architecture (uniprocessor, multicore), as well as task constraints like critical sections, precedence constraints, self-suspension, etc. Since the result is based only on the releases and deadlines, it is independent from any other parameter. Note that we do not claim that the given interval is minimal, but it is an upper bound for any cycle of any feasible schedule provided by any deterministic and memoryless scheduler.

Published
2013

11. Predictability of Fixed-Job Priority Schedulers on Heterogeneous Multiprocessor Real-Time Systems

Author

Cucu-Grosjean, Liliana and Goossens, Joël

Subjects
Computer Science - Operating Systems
Abstract

The multiprocessor Fixed-Job Priority (FJP) scheduling of real-time systems is studied. An important property for the schedulability analysis, the predictability (regardless to the execution times), is studied for heterogeneous multiprocessor platforms. Our main contribution is to show that any FJP schedulers are predictable on unrelated platforms. A convenient consequence is the fact that any FJP schedulers are predictable on uniform multiprocessors.

Published
2009

15. Towards a new task model for merging control theory and real-time scheduling problems

Author

Hawila, Ismail, Cucu-Grosjean, Liliana, Amor, Slim, Sorel, Yves, StatInf, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Schedulability analysis, Control systems, Precedence constraints, [INFO]Computer Science [cs], Sensitivity analysis, Real-time systems
Abstract

International audience; Existing task models for cyber-physical systems have been proposed to merge the requirements associated to the stability of control tasks managing physical components, and to the schedulability of these tasks. Nevertheless, these models stay to a high level without covering concerns like the data and/or precedence constraints between different control tasks as well as non-control tasks, the impact of period variation between dependent control tasks and the impact of data constraints on the execution times of control tasks. Our current work concentrates on discussing properties of a new task model in order to cover these concerns.

Published
2023

19. RTNS 2022: The 30th International Conference on Real-Time Networks and Systems

Author

Abdeddaïm, Yasmina, Cucu-Grosjean, Liliana, Nelissen, Geoffrey, Pautet, Laurent, Université Gustave Eiffel, Laboratoire d'Informatique Gaspard-Monge (LIGM), École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Université Gustave Eiffel, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Eindhoven University of Technology [Eindhoven] (TU/e), Institut Polytechnique de Paris (IP Paris), Département Informatique et Réseaux (INFRES), Télécom ParisTech, Autonomic and Critical Embedded Systems (ACES), Laboratoire Traitement et Communication de l'Information (LTCI), and Institut Mines-Télécom [Paris] (IMT)-Télécom Paris-Institut Mines-Télécom [Paris] (IMT)-Télécom Paris

Subjects
[INFO]Computer Science [cs]
Published
2022
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20. Work in Progress: KDBench - towards open source benchmarks for measurement-based multicore WCET estimators

Author

Khazen, Marwan Wehaiba El, Zagalo, Kevin, Clarke, Hadrien, Mezouak, Mehdi, Abdeddaïm, Yasmina, Bar-Hen, Avner, Amor, Slim Ben, Bennour, Rihab, Gogonel, Adriana, Kougblenou, Kossivi, Sorel, Yves, Cucu-Grosjean, Liliana, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire d'Informatique Gaspard-Monge (LIGM), École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Université Gustave Eiffel, ESIEE Paris, Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), StatInf, and PSPC-region 2022 STARTREC

Subjects
Measurement-based WCET estimation, Benchmarks, [INFO]Computer Science [cs]
Abstract

International audience; The real-time systems community is facing the lack of benchmarks adapted to measurement-based worst-case execution time (WCET) estimators. We provide in this paper first steps towards such benchmarks by proposing them for single core microcontrollers, while we leave as future work the migration to multicore microcontrollers. The considered benchmarks are the programs of an open source drone autopilot. We conclude the paper by underlining the main difficulties of such migration.

Published
2022
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21. STARTREC: Verification of a safety-critical system for autonomous vehicles

Author

Khazen, Marwan Wehaiba El, Amor, Slim Ben, Cucu-Grosjean, Liliana, Dumérat, Arnaud, Jean, Xavier, Kougblenou, Kossivi, Monate, Benjamin, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), StatInf, EasyMile SAS, TrustInSoft (TIS ), and STARTREC

Subjects
Formal verification, Autonomous vehicles, Timing verification, [INFO]Computer Science [cs]
Abstract

International audience; In this paper, we present our ongoing work on verification activities of the software used in a safety-critical embedded system dedicated to autonomous vehicles. These activities are focused on the use of formal methods for the verification of functional properties on the embedded code, and statistical methods for the analysis of its Worst-Case Execution Time (WCET). The project's goal is to address some technical barriers of software verification that will impact the safety demonstration of future autonomous driving systems. These barriers are challenging because of the high complexity of an embedded hardware and software, and appeal for methods and tools reaching the highest level of rigorousness.

Published
2022

25. Aircraft Numerical 'Twin': A Time Series Regression Competition

Author

Pavao, Adrien, Guyon, Isabelle, Stéphane, Nachar, Lebeau, Fabrice, Ghienne, Martin, Platon, Ludovic, Barbagelata, Tristan, Escamilla, Pierre, Mzali, Sana, Liao, Meng, Lassonde, Sylvain, Braun, Antonin, Amor, Slim, Cucu-Grosjean, Liliana, Wehaiba, Marwan, Bar-Hen, Avner, Gogonel, Adriana, Cheikh, Alaeddine, Duda, Marc, Laugel, Julien, Marauri, Mathieu, Souissi, Mhamed, Lecerf, Théo, Elion, Mehdi, Tabti, Sonia, Budynek, Julien, Le Bouteiller, Pauline, Penon, Antonin, Lasseri, Raphaël-David, Ripoche, Julien, Epalle, Thomas, TAckling the Underspecified (TAU), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), A&O (Apprentissage et Optimisation) (A&O), Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Science des Données (SDD), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Algorithmes, Apprentissage et Calcul (AAC), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Science des Données (SDD), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Algorithmes, Apprentissage et Calcul (AAC), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Dassault Aviation, Laboratoire QUARTZ (QUARTZ ), Université Paris 8 Vincennes-Saint-Denis (UP8)-Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA)-ISAE-Supméca Institut Supérieur de Mécanique de Paris (ISAE-Supméca), ISAE-Supméca Institut Supérieur de Mécanique de Paris (ISAE-Supméca), Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), MFG Labs, Fieldbox AI, Magic LEMP, We would like to warmly thank the Ile-de-France region for the support and funding of this project. This work was also supported by the ANR (Agence Nationale de la Recherche, National Agency for Research) un-der AI chair of excellence HUMANIA, grant number Project-ANR-19-CHIA-0022, ANR-19-CHIA-0022,HUMANIA,Intelligence Artificielle pour Tous(2019), and Institut Supérieur de Mécanique de Paris (ISAE-Supméca)

Subjects
[SPI]Engineering Sciences [physics], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Time series regression, Machine learning, Deep learning, Gradient boosted trees, ComputerApplications_COMPUTERSINOTHERSYSTEMS, Aeronautics, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; This paper presents the design and analysis of a data science competition on a problem of time series regression from aeronautics data. For the purpose of performing predictive maintenance, aviation companies seek to create aircraft "numerical twins", which are programs capable of accurately predicting strains at strategic positions in various body parts of the aircraft. Given a number of input parameters (sensor data) recorded in sequence during the flight, the competition participants had to predict output values (gauges), also recorded sequentially during test flights, but not recorded during regular flights. The competition data included hundreds of complete flights. It was a code submission competition with complete blind testing of algorithms. The results indicate that such a problem can be effectively solved with gradient boosted trees, after preprocessing and feature engineering. Deep learning methods did not prove as efficient. Index Terms-aeronautics, time series regression, machine learning, deep learning, gradient boosted trees.

Published
2021
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26. Work in Progress : Towards representative measurement protocols

Author

Kougblenou , Kossivi, Bennour, Rihab, Gogonel, Adriana, Cucu-Grosjean, Liliana, StatInf, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Cucu-Grosjean, Liliana

Subjects
[INFO.INFO-ES]Computer Science [cs]/Embedded Systems, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

International audience

Published
2020

27. Work in Progress Lessons learnt from creating Extreme Value Libraries in Python

Author

Wehaiba El Khazen, Marwan, Gogonel, Adriana, Cucu-Grosjean, Liliana, StatInf, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Cucu-Grosjean, Liliana

Subjects
[INFO.INFO-ES]Computer Science [cs]/Embedded Systems, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

International audience

Published
2020

28. On the Selection of Relevant Hardware Events for Explaining Execution Time Behavior

Author

Andrade, Tadeu Nogueira C., Lima, George, Lima, Veronica Maria Cadena, Abdeddaim, Yasmina, Cucu-Grosjean, Liliana, Universidade Federal da Bahia (UFBA), ESIEE Paris, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), EA KEPLER, and PSPC STARTREC

Subjects
Measurement-based timing analysis, Hardware events, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, Multi-core architectures, Real-time systems
Abstract

International audience; Estimating safe upper bounds on task execution times is required in the design of predictable real-time systems. When multi-core, instruction pipeline, branch prediction, or cache memory are in place, due to the considerable complexity static timing analysis faces, measurement-based timing analysis (MBTA) is a more tractable option. MBTA estimates upper bounds on execution times using data measured under the execution of representative scenarios. In this context, it is paramount understanding not only how the task execution time is affected during its execution but also what kind of interference the task is sensitive to. Events such as cache misses or pipeline stalls, for example, may lead to large variability in task execution times. Based on the fact that current platforms offer Performance Monitoring Units (PMUs) capable of counting hardware-level event occurrences, in this paper, we focus on the problem of selecting the events that have the most impact on task execution with the goal of enriching the collected information to better support MBTA. Unfortunately, PMU usually have a limited number of monitoring registers, making them unable to monitor all events at once. Our approach describes how to carry out the events selection even under this limitation. Results from our experiments, considering 15 different programs running on a Raspberry Pi, indicate that five selected events can explain the execution behavior of the programs with reasonable accuracy.

Published
2021
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30. Aircraft Numerical “Twin”: A Time Series Regression Competition

Author

Pavao, Adrien, primary, Guyon, Isabelle, additional, Stephane, Nachar, additional, Lebeau, Fabrice, additional, Ghienne, Martin, additional, Platon, Ludovic, additional, Barbagelata, Tristan, additional, Escamilla, Pierre, additional, Mzali, Sana, additional, Liao, Meng, additional, Lassonde, Sylvain, additional, Braun, Antonin, additional, Amor, Slim Ben, additional, Cucu-Grosjean, Liliana, additional, Wehaiba, Marwan, additional, Bar-Hen, Avner, additional, Gogonel, Adriana, additional, Cheikh, Alaeddine Ben, additional, Duda, Marc, additional, Laugel, Julien, additional, Marauri, Mathieu, additional, Souissi, Mhamed, additional, Lecerf, Theo, additional, Elion, Mehdi, additional, Tabtill, Sonia, additional, Budynek, Julien, additional, Bouteiller, Pauline Le, additional, Penon, Antonin, additional, Lasseri, Raphael-David, additional, Ripoche, Julien, additional, and Epalle, Thomas, additional

Published
2021
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39. Response time analysis for precedence constrained and partitioned multiprocessor scheduled tasks

Author

Ben-Amor, Slim, Cucu-Grosjean, Liliana, Models and methods of analysis and optimization for systems with real-time and embedded contraints (AOSTE2 ), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Ceos, CEOS.FR, and Cucu-Grosjean, Liliana

Subjects
multiprocessor, partitioned scheduling, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

International audience

Published
2018

40. Probabilistic parallel real-time tasks model on multiprocessor platform

Author

Ben-Amor, Slim, Cucu-Grosjean, Liliana, Models and methods of analysis and optimization for systems with real-time and embedded contraints (AOSTE2 ), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), FUI CEOS, and Cucu-Grosjean, Liliana

Subjects
[INFO.INFO-ES]Computer Science [cs]/Embedded Systems, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

International audience

Published
2018

41. Towards temporal constraints in self driving cars

Author

Ntaryamira, Evariste, Maxim, Cristian, Flores, Carlos, Cucu-Grosjean, Liliana, Models and methods of analysis and optimization for systems with real-time and embedded contraints (AOSTE2 ), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Robotics & Intelligent Transportation Systems (RITS), Ambassade de France au Burundi, and Cucu-Grosjean, Liliana

Subjects
[INFO.INFO-ES]Computer Science [cs]/Embedded Systems, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

International audience

Published
2018

43. Time Triggered Offline Scheduling of Data Dependent Real-Time Tasks Accounting for the Preemption and Scheduler Cost

Author

Sorel, Yves, Ndoye, Falou, Talaboulma, Walid, Mezouak, Mehdi, Cucu-Grosjean, Liliana, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), ESITEC, Groupe Supdeco Dakar, and Inria Paris

Subjects
Tâches avec dépendances de données, Coût de la préemption, Ordonnancement temps réel, Real-time scheduling, Coût de l’ordonnanceur, Ordonnanceur déclanché par le temps, Scheduler cost, Preemption cost, Data dependent tasks, Analyse d’ordonnançabilité temps réel hors ligne, Critical embedded system, Time triggered scheduler, ARM Cortex- M4 processor, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, Processeur ARM Cortex-M4, [INFO.INFO-OS]Computer Science [cs]/Operating Systems [cs.OS], Système embarqué critique, Offline real-time schedulability analysis
Abstract

Time critical embedded systems usually consist of a set of periodic data dependentreal-time tasks issued from a functional specification achieved with a block diagram language. Al-though non-preemptive real-time scheduling is safer than preemptive real-time scheduling in a timecritical context, preemptive real-time scheduling may provide better scheduling ratio. However,this better scheduling ratio comes with a cost related to the preemption, and a non precise determi-mation of this cost can prevent to satisfy real-time constraints. In this paper we propose an offlineschedulability analysis for a set of data dependent periodic tasks which precisely accounts for thepreemption and scheduler cost. This analysis produces a scheduling table that is exploited by atime triggered offline scheduler. We show that this scheduler, implemented on an ARM Cortex-M4bare metal uniprocessor for which the preemption and scheduler cost is precisely determined, isable to schedule correctly a set of tasks that can miss some deadlines if the preemption and sched-uler cost is incorrectly determined. Therefore, such offline scheduling and scheduler approach isperfectly suited for time critical embedded systems.; Les systèmes temps réel critiques consistent en général en un ensemble de tâches périodiques avec des dépendances de données issu d’une spécification fonctionnelle réalisée à l’aide d’un langage de type schéma bloc. Bien que l’ordonnancement temps réel non préemptif soit plus sûr que l’ordonnancement temps réel préemptif dans un contexte critique, l’ordonnancement temps réel préemptif peut avoir de meilleurs taux d’ordonnancement. Cependant, cela a pour conséquence un coût associé à la préemption. Ainsi, la non prise en compte précise de ce coût peut empêcher de satisfaire les contraintes temps réel. Dans ce papier nous proposons une analyse d’ordonnançabilité pour un ensemble de tâches avec des dépendances de données qui prend en compte précisément le coût de la préemption et de l’ordonnanceur. Cette approche produit une table d’ordonnancement qui est exploitée par un ordonnanceur hors ligne déclanché par le temps. Nous montrons que cet ordonnanceur, implanté sur un monoprocesseur nu ARM Cortex-M4 pour lequel le coût de la préemption et de l’ordonnanceur est précisément déterminé, est capable d’ordonnancer correctement un ensemble de tâches dont certaines peuvent rater leur échéance si ce coût n’est pas correctement déterminé. Ainsi, cette approche hors ligne d’ordonnancement et d’ordonnanceur est parfaitement adaptée pour les systèmes temps réel critiques.

Published
2019

44. The temporal correlation of data in a multirate system

Author

Ntaryamira, Evariste, Maxim, Cristian, Cucu-Grosjean, Liliana, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), IRT SystemX (IRT SystemX), and IRT SystemX

Subjects
Data, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Scheduling, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Real-time
Abstract

International audience; Technologies within embedded real-time systems are continuously evolving making them intelligent; at some point they can achieve targeted functions autonomously. Such systems are extended with capability of sensing the surrounding environment and deciding on their own. In addition to the feasible scheduling policy, the correctness of such decisions highly depends on the quality of the used input data. Thereby, the data management within such systems must fulfill some properties in order to guarantee their correct functioning. In this paper we address the problem of data temporal correlation and validity when the system scheduling properties are defined. We present preliminary results on expected properties of the architectures and underline future work.

Published
2019

45. Towards statistical estimation of worst case inter-core communications

Author

Revuz, Anselme, Cucu-Grosjean, Liliana, Models and methods of analysis and optimization for systems with real-time and embedded contraints (AOSTE2 ), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Cucu-Grosjean, Liliana

Subjects
[INFO]Computer Science [cs], [INFO] Computer Science [cs]
Abstract

International audience; Statistical approaches have been recently received increased effort from the real-time community. While taking into account that worst case scenarios are rare events, the statistical approaches may decrease considerable the pessimism of a real-time analysis. In this paper we present first results on the statistical estimation of inter-core communications on a multicore platform. Our preliminary results are based on the utilization of the Extreme Value Theory and they are promising as they allow to detect insufficient observations of the communications.

Published
2017

46. Work-in-Progress: System-wide DVFS for real-time systems with probabilistic parameters

Author

Medina, Roberto, Cucu-Grosjean, Liliana, Medina, Roberto, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
[INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

International audience; Power consumption and the ever-increasing service demand are key issues that real-time embedded systems are facing nowadays. Approaches based on Dynamic Voltage and Frequency Scaling (DVFS) are capable of reducing the energy consumed by processors while still guaranteeing real-time constraints. In this paper we present short-comes on the state-of-the-art techniques that need to be leveraged in order to be more effective when reducing energy consumption: our experimental results clearly show that tasks' execution time is not proportional to processor speed, and that DVFS techniques could also be applied on other components like bus and memory without compromising time constraints. We also discuss the applicability of real-time probabilistic systems and DVFS, and argue that by adopting a frequency-aware model, we can (i) capture more detailed behaviors of tasks w.r.t. processor speeds and (ii) apply DVFS techniques to gain in energy consumption.

Published
2019

47. Probabilistic Analysis

Author

Maxim, Dorin, Cucu-Grosjean, Liliana, Davis, Robert, Université de Lorraine (UL), Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and University of York [York, UK]

Subjects
010201 computation theory & mathematics, 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, 020202 computer hardware & architecture
Abstract

International audience; The classical model of a real-time system consists of a number of tasks, each of which has an execution time which is upper bounded by a constant, referred to as the worst-case execution time (WCET). Further, jobs of each task execute periodically or sporadically, subject to some minimum inter-arrival time. Task execution is controlled by a real-time scheduler that determines, at any given time, which of the ready jobs the processor will execute. For such a model, schedulability analysis provides an a priori mathematical verification indicating whether or not all of the jobs of each task can be guaranteed to meet their deadlines under the particular scheduling policy used. This analysis is typically achieved by determining the worst-case scenario that leads to the worst-case response time (from the release to the completion of any job of the task), calculating the worst-case response time, and comparing it with the task’s deadline. Probabilistic real-time systems differ from this classical model in two main ways. Firstly, at least one parameter of the tasks (e.g., execution time) is modeled as a random variable, i.e., described by a probability distribution. Secondly, rather than requiring an absolute guarantee that all deadlines must be met, timing constraints are specified in terms of a threshold on the acceptable probability of a deadline miss for each task. This chapter focuses on research into scheduling and specifically schedulability analysis for probabilistic real-time systems.

Published
2019
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48. Time4Sys – Integrating Timing Verification in your Engineering Practices

Author

Fejoz, Loïc, Havet, Lionel, Didier, Aurélien, Viaud, Benoit, Bui Long, Anh-Toan, Nguyen, Thanh Dat, Ouhammou, Yassine, Grolleau, Emmanuel, Gogonel, Adriana, Maxim, Cristian, Cucu-Grosjean, Liliana, Henia, Rafik, Rioux, Laurent, Sordon, Nicolas, Ayache, Nicolas, Rehm, Joris, Realtime-at-Work (RTaW), ARTAL Technologies, Laboratoire d'Informatique et d'Automatique pour les Systèmes (LIAS), Université de Poitiers-ENSMA, Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Models and methods of analysis and optimization for systems with real-time and embedded contraints (AOSTE2 ), Thales Research and Technology [Palaiseau], THALES, ClearSy Systems Engineering, FUI Waruna, and THALES [France]

Subjects
[INFO.INFO-ES]Computer Science [cs]/Embedded Systems, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

49. Ensuring data freshness for periodic real-time tasks

Author

Ntaryamira, Evariste, Maxim, Cristian, Cucu-Grosjean, Liliana, Models and methods of analysis and optimization for systems with real-time and embedded contraints (AOSTE2 ), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Adapter le raisonnement pire cas à différentes criticités (KOPERNIC), Bourse de l'Ambassade de France au Burundi, and NTARYAMIRA, Evariste

Subjects
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

International audience; Automotive systems are composed of embedded applications which are continuously exchanging real-time data. Exchanged data are then propagated within a list of applications involved at different rates in the definition of a function. Different rates of executions for the applications provoke over-and/or under-sampling of data and the age of the data has an obvious impact on the driving decisions. Ensuring that the appropriate data are consumed by an application motivates to maintain the freshness or the temporal validity of real-time data. In this paper we propose a method calculating the freshness of the data for real-time systems where multi-rate sampling of data is considered.

Published
2018

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