Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Real-Time Systems
Erschienen in: Real-Time Systems 2/2018

28.02.2018

Multi-objective design exploration approach for Ravenscar real-time systems

verfasst von: Rahma Bouaziz, Laurent Lemarchand, Frank Singhoff, Bechir Zalila, Mohamed Jmaiel

Erschienen in: Real-Time Systems | Ausgabe 2/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This article deals with the design exploration and verification of real-time critical systems. Assigning the functions to the tasks of the target real-time operating system is a part of the design process. Finding a suitable design involves many important design decisions that have a strong impact on the system quality criteria. However, with the increasing complexity and scale of today’s systems and the large number of possible design solutions, making design decisions while balancing conflicting quality criteria becomes error-prone and unmanageable for designers. We propose an automated method using a multi-objective evolutionary algorithm guided by an architectural clustering technique. This method allows designers to search the design space for schedulable solutions with respect to multiple competing performance criteria. To assess our method, several evaluations were performed. One of them shows that we were able to produce the exact optimal solution sets for \(55\%\) of the studied problem instances.
Vorheriger Artikel Patmos: a time-predictable microprocessor
Nächster Artikel Enhancing timeliness and saving power in real-time databases

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Fußnoten
1
AUTomotive Open System ARchitecture (AUTOSAR): an open standard for automotive software development. It provides a standard architecture, application interfaces and a methodology that are adopted by the automotive industry.
 
2
A situation in which a task is blocked by a lower-priority task.
 
3
A situation in which two or more tasks are waiting indefinitely for each other.
 
4
The choice of the constant is arbitrary.
 
6
A feasibility test is an analytical method which usually allows users to compute performance criteria in order to assess if task deadlines will be met.
 
7
Due to the significant time required to solve a test instance, the number of test instances used in this experiment is limited to 100.
 
Literatur
Audsley N, Burns A, Richardson M, Tindell K, Wellings AJ (1993) Applying new scheduling theory to static priority preemptive scheduling. Softw Eng J 8(5):284–292CrossRef
Bandyopadhyay S, Saha S (2013) Some single- and multiobjective optimization techniques. Unsupervised classification. Springer, Berlin, pp 17–58CrossRef
Bartolini C, Lipari G, Di Natale M (2005) From functional blocks to the synthesis of the architectural model in embedded real-time applications. In: Proceedings of the \(11^{th}\) IEEE real time and embedded technology and applications symposium, pp 458–467
Bertout A, Forget J, Olejnik R (2014) Minimizing a real-time task set through task clustering. In: Proceedings of the 22nd international conference on real-time networks and systems. ACM, pp 23–31
Bouaziz R, Lemarchand L, Singhoff F, Zalila B, Jmaiel M (2015) Architecture exploration of real-time systems based on multi-objective optimization. In: Proceedings of the 20th international conference on engineering of complex computer systems, pp 1–10
Bouaziz R, Lemarchand L, Singhoff F, Zalila B, Jmaiel M (2016) Efficient parallel multi-objective optimization for real-time systems software design exploration. In: Proceedings of the 27th international symposium on rapid system prototyping: shortening the path from specification to prototype. ACM, New York, pp 58–64
Burns A (1999) The ravenscar profile. ACM SIGAda Ada Lett 19(4):49–52CrossRef
Buttazzo G (2011) Hard real-time computing systems: predictable scheduling algorithms and applications, vol 24. Springer, BerlinMATH
Carlsson C, Fullér R (1995) Multiple criteria decision making: the case for interdependence. Comput. Oper. Res. 22(3):251–260CrossRefMATH
Coello Coello CA, Lamont GB, Veldhuizen DAV (2007) Evolutionary algorithms for solving multi-objective problems. Springer, BerlinMATH
Deb K (2001) Multi-objective optimization using evolutionary algorithms, vol 16. Wiley, New YorkMATH
Deb K, Saxena D (2006) Searching for pareto-optimal solutions through dimensionality reduction for certain large-dimensional multi-objective optimization problems. In: Proceedings of the world congress on computational intelligence, pp 3352–3360
Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans Evolut Comput 6(2):182–197CrossRef
Feiler PH, Gluch DP (2012) Model-based engineering with AADL: an Introduction to the SAE architecture analysis & design language. Addison-Wesley, Upper Saddle River
Fonseca CM, Knowles JD, Thiele L, Zitzler E (2005) A tutorial on the performance assessment of stochastic multiobjective optimizers. In: Proceedings of the 3rd international conference on evolutionary multi-criterion optimization, vol 216, p 240
Fonseca CM, Paquete L, López-Ibánez M (2006) An improved dimension-sweep algorithm for the hypervolume indicator. In: IEEE congress on evolutionary computation. IEEE, pp 1157–1163
Fürst S, Mössinger J, Bunzel S, Weber T, Kirschke-Biller F, Heitkämper P, Kinkelin G, Nishikawa K, Lange K (2009) Autosar—a worldwide standard is on the road. In: Proceedings of the 14th international VDI congress electronic systems for vehicles, Baden-Baden, vol 62
Gal T, Hanne T (1999) Consequences of dropping nonessential objectives for the application of mcdm methods. Eur J Oper Res 119(2):373–378CrossRefMATH
Goossens J, Macq C (2001) Limitation of the hyper-period in real-time periodic task set generation. In: Proceedings of the real-time embedded systems
Goossens J, Grolleau E, Cucu-Grosjean L (2016) Periodicity of real-time schedules for dependent periodic tasks on identical multiprocessor platforms. J Real Time Syst 52(6):808–832CrossRefMATH
Haubelt C, Gamenik J, Teich J (2005) Initial population construction for convergence improvement of moeas. In: Proceedings of the 3rd international conference on evolutionary multi-criterion optimization (EMO’05). Springer, Berlin, pp 191–205
Klein MH, Ralya T, Pollak B, Obenza R, Harbour MG (1993) A practitioners handbook for real-time analysis: guide to rate monotonic analysis for real-time systems. Springer, New YorkCrossRef
Koziolek A, Koziolek H, Reussner R (2011) Peropteryx: automated application of tactics in multi-objective software architecture optimization. In: Proceedings of the joint ACM SIGSOFT conference—QoSA and ACM SIGSOFT symposium—ISARCS on Quality of software architectures—QoSA and architecting critical systems—ISARCS. ACM, pp 33–42
Leung JYT, Whitehead J (1982) On the complexity of fixed-priority scheduling of periodic, real-time tasks. Perform Eval 2(4):237–250MathSciNetCrossRefMATH
Li R, Etemaadi R, Emmerich MT, Chaudron MR (2011) An evolutionary multiobjective optimization approach to component-based software architecture design. In: IEEE congress on evolutionary computation. IEEE, pp 432–439
López Jaimes A, Coello Coello CA, Chakraborty D (2008) Objective reduction using a feature selection technique. In: Proceedings of the 10th annual conference on genetic and evolutionary computation. ACM, pp 673–680
López Jaimes A, Coello Coello CA, Urías Barrientos JE (2009) Online objective reduction to deal with many-objective problems. Springer, Berlin, pp 423–437
López Jaimes A, Coello Coello CA, Aguirre H, Tanaka K (2014) Objective space partitioning using conflict information for solving many-objective problems. Inf Sci 268:305–327MathSciNetCrossRefMATH
McCormick JW, Singhoff F, Hugues J (2011) Building parallel, embedded, and real-time applications with Ada, vol 1. Cambridge University Press, CambridgeCrossRef
Mehiaoui A, Wozniak E, Tucci-Piergiovanni S, Mraidha C, Di Natale M, Zeng H, Babau JP, Lemarchand L, Gerard S (2013) A two-step optimization technique for functions placement, partitioning, and priority assignment in distributed systems. ACM SIGPLAN Not 48(5):121–132CrossRef
Monot A, Navet N, Bavoux B, Simonot-Lion F (2012) Multisource software on multicore automotive ecuscombining runnable sequencing with task scheduling. IEEE Trans Ind Electron 59(10):3934–3942CrossRef
Mraidha C, Tucci-Piergiovanni S, Gerard S (2011) Optimum: a marte-based methodology for schedulability analysis at early design stages. ACM SIGSOFT Softw Eng Notes 36(1):1–8CrossRef
Mzid R, Mraidha C, Mehiaoui A, Tucci-Piergiovanni S, Babau JP, Abid M (2013) Dpmp: a software pattern for real-time tasks merge. In: European conference on modelling foundations and applications, vol 7949. Springer, Berlin, pp 101–117
Pagetti C, Forget J, Boniol F, Cordovilla M, Lesens D (2011) Multi-task implementation of multi-periodic synchronous programs. Discret Event Dyn Syst 21(3):307–338MathSciNetCrossRefMATH
Purshouse RC, Fleming PJ (2007) On the evolutionary optimization of many conflicting objectives. IEEE Trans Evol Comput 11(6):770–784CrossRef
Rahmoun S, Borde E, Pautet L (2015a) Automatic selection and composition of model transformations alternatives using evolutionary algorithms. In: Proceedings of the 9th European conference on software architecture workshops. ACM, p 25
Rahmoun S, Borde E, Pautet L (2015b) Multi-objectives refinement of AADL models for the synthesis embedded systems (mu-RAMSES). In: Proceedings of the 20th international conference on engineering of complex computer systems, pp 21–30
Saidi SE, Cotard S, Chaaban K, Marteil K (2015) An ILP approach for mapping AUTOSAR runnables on multi-core architectures. In: Proceedings of the 2015 workshop on rapid simulation and performance evaluation: methods and tools. ACM, p 6
Santinelli L, Puffitsch W, Dumerat A, Boniol F, Pagetti C, Victor J (2014) A grouping approach to task scheduling with functional and non-functional requirements. In: Proceedings of the 2nd embedded real-time software and systems
Saxena DK, Duro JA, Tiwari A, Deb K, Zhang Q (2013) Objective reduction in many-objective optimization: linear and nonlinear algorithms. IEEE Trans Evol Comput 17(1):77–99CrossRef
Scheickl O, Rudorfer M (2008) Automotive real-time development using a timing-augmented AUTOSAR specification. In: Proceedings of the 4th international congress on embedded real-time systems
Sha L, Rajkumar R, Lehoczky JP (1990) Priority inheritance protocols: an approach to real-time synchronization. IEEE Trans Comput 39(9):1175–1185MathSciNetCrossRef
Singhoff F, Legrand J, Nana L, Marcé L (2004) Cheddar: a flexible real time scheduling framework. Ada Lett XXIV(4):1–8CrossRef
Singhoff F, Plantec A, Rubini S, Tran H, Gaudel V, Boukhobza J, Lemarchand L, Li S, Borde E, Pautet L et al (2015) Teaching real-time scheduling analysis with cheddar. In: 9ème édition de l’Ecole d’Eté Temps Réel
Stankovic JA (1988) Misconceptions about real-time computing: a serious problem for next-generation systems. Computer 21(10):10–19CrossRef
Taft ST, Duff RA, Brukardt RL, Ploedereder E, Leroy P, Schonberg E (2014) Ada 2012 reference manual. Language and standard libraries: international standard ISO/IEC 8652/2012 (E), vol 8339. Springer, Berlin
Van Veldhuizen DA, Lamont GB (1998) Multiobjective evolutionary algorithm research: a history and analysis. Technical Report TR-98-03, Department of Electrical and Computer Engineering, Air France Institute of Technology, Ohio
Westfall PH, Young SS (1993) Resampling-based multiple testing: examples and methods for p-value adjustment, vol 279. Wiley, New YorkMATH
Wozniak E, Mehiaoui A, Mraidha C, Tucci-Piergiovanni S, Gerard S (2013) An optimization approach for the synthesis of autosar architectures. In: Proceedings of the 18th IEEE conference on emerging technologies & factory automation. IEEE, pp 1–10
Zhang Q, Zhou A, Zhao S, Suganthan PN, Liu W, Tiwari S (2008) Multiobjective optimization test instances for the CEC 2009 special session and competition. University of Essex, Colchester, UK and Nanyang technological University, Singapore, special session on performance assessment of multi-objective optimization algorithms, technical report 264
Zitzler E, Thiele L (1998) Multiobjective optimization using evolutionary algorithms-a comparative case study. In: Proceedings of the international conference on parallel problem solving from nature. Springer, Berlin, pp 292–301
Metadaten
Titel
Multi-objective design exploration approach for Ravenscar real-time systems
verfasst von
Rahma Bouaziz
Laurent Lemarchand
Frank Singhoff
Bechir Zalila
Mohamed Jmaiel
Publikationsdatum
28.02.2018
Verlag
Springer US
Erschienen in
Real-Time Systems / Ausgabe 2/2018
Print ISSN: 0922-6443
Elektronische ISSN: 1573-1383
DOI
https://doi.org/10.1007/s11241-018-9299-6

Weitere Artikel der Ausgabe 2/2018

Real-Time Systems 2/2018 Zur Ausgabe

OriginalPaper

Enhancing timeliness and saving power in real-time databases

OriginalPaper

Delay-dependent partial order reduction technique for real time systems

OriginalPaper

Multi-rate fluid scheduling of mixed-criticality systems on multiprocessors

OriginalPaper

On the analysis of random replacement caches using static probabilistic timing methods for multi-path programs

OriginalPaper

Patmos: a time-predictable microprocessor