1,778 research outputs found
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
Building a MultiAgent System from a User Workflow Specification
This paper provides a methodology to build
a MultiAgent System (MAS) described in terms of interactive
components from a domain-specic User Workow
Specication (UWS). We use a Petri nets-based notation
to describe workow specications. This, besides using a
familiar and well-studied notation, guarantees an highlevel
of description and independence with more concrete
vendor-specic process denition languages. In order to
bridge the gap between workow specications and MASs,
we exploit other intermediate Petri nets-based notations.
Transformation rules are given to translate a notation to
another. The generated agent-based application implements
the original workow specication. Run-time support is
provided by a middleware suitable for the execution of the
generated code
Eighth Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools, Aarhus, Denmark, October 22-24, 2007
This booklet contains the proceedings of the Eighth Workshop on Practical Use of Coloured Petri Nets and the CPN Tools, October 22-24, 2007. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark. The papers are also available in electronic form via the web pages: http://www.daimi.au.dk/CPnets/workshop0
Petri net-based approach for web service automation resource coordination
In industrial automation, control systems and mechatronic devices are from
diverse nature, supplied by different manufacturers and made of different
technologies. The adoption of web services principles in an automated
production system satisfies some requirements, namely the interoperability of
such heterogeneous and distributed environments and the basis for flexibility
and reconfigurability. Manufacturing processes require to access resources at
different precedence levels and time instances, but in the other way resources
may also be shared by different processes. A major challenge is then how
individual services may interact, coordinating their activities. Petri nets may be
used to describe complex system behaviour and therefore also applied to
coordinate such systems. The paper introduces a Petri net based approach for the
design, analysis and coordination of systems developed using web services to
represent individual and autonomous resources. For this purpose, it is presented
a Petri nets computational tool to support the design, validation and coordination
of web service based automation systems.info:eu-repo/semantics/publishedVersio
Recent advances in petri nets and concurrency
CEUR Workshop Proceeding
Fine-Grained Workflow Interoperability in Life Sciences
In den vergangenen Jahrzehnten führten Fortschritte in den Schlüsseltechnologien der Lebenswissenschaften zu einer exponentiellen Zunahme der zur Verfügung stehenden biologischen Daten. Um Ergebnisse zeitnah generieren zu können werden sowohl spezialisierte Rechensystem als auch Programmierfähigkeiten benötigt: Desktopcomputer oder monolithische Ansätze sind weder in der Lage mit dem Wachstum der verfügbaren biologischen Daten noch mit der Komplexität der Analysetechniken Schritt zu halten.
Workflows erlauben diesem Trend durch Parallelisierungsansätzen und verteilten Rechensystemen entgegenzuwirken. Ihre transparenten Abläufe, gegeben durch ihre klar definierten Strukturen, ebenso ihre Wiederholbarkeit, erfüllen die Standards der Reproduzierbarkeit, welche an wissenschaftliche Methoden gestellt werden.
Eines der Ziele unserer Arbeit ist es Forschern beim Bedienen von Rechensystemen zu unterstĂĽtzen, ohne dass Programmierkenntnisse notwendig sind. DafĂĽr wurde eine Sammlung von Tools entwickelt, welche jedes Kommandozeilenprogramm in ein Workflowsystem integrieren kann. Ohne weitere Anpassungen kann unser Programm zwei weit verbreitete Workflowsysteme unterstĂĽtzen. Unser modularer Entwurf erlaubt zudem UnterstĂĽtzung fĂĽr weitere Workflowmaschinen hinzuzufĂĽgen.
Basierend auf der Bedeutung von frühen und robusten Workflowentwürfen, haben wir außerdem eine wohl etablierte Desktop–basierte Analyseplattform erweitert. Diese enthält über 2.000 Aufgaben, wobei jede als Baustein in einem Workflow fungiert. Die Plattform erlaubt einfache Entwicklung neuer Aufgaben und die Integration externer Kommandozeilenprogramme. In dieser Arbeit wurde ein Plugin zur Konvertierung entwickelt, welches nutzerfreundliche Mechanismen bereitstellt, um Workflows auf verteilten Hochleistungsrechensystemen auszuführen—eine Aufgabe, die sonst technische Kenntnisse erfordert, die gewöhnlich nicht zum Anforderungsprofil eines Lebenswissenschaftlers gehören.
Unsere Konverter–Erweiterung generiert quasi identische Versionen desselben Workflows, welche im Anschluss auf leistungsfähigen Berechnungsressourcen ausgeführt werden können. Infolgedessen werden nicht nur die Möglichkeiten von verteilten hochperformanten Rechensystemen sowie die Bequemlichkeit eines für Desktopcomputer entwickelte Workflowsystems ausgenutzt, sondern zusätzlich werden Berechnungsbeschränkungen von Desktopcomputern und die steile Lernkurve, die mit dem Workflowentwurf auf verteilten Systemen verbunden ist, umgangen. Unser Konverter–Plugin hat sofortige Anwendung für Forscher. Wir zeigen dies in drei für die Lebenswissenschaften relevanten Anwendungsbeispielen: Strukturelle Bioinformatik, Immuninformatik, und Metabolomik.Recent decades have witnessed an exponential increase of available biological data due to advances in key technologies for life sciences. Specialized computing resources and scripting skills are now required to deliver results in a timely fashion: desktop computers or monolithic approaches can no longer keep pace with neither the growth of available biological data nor the complexity of analysis techniques.
Workflows offer an accessible way to counter against this trend by facilitating parallelization and distribution of computations. Given their structured and repeatable nature, workflows also provide a transparent process to satisfy strict reproducibility standards required by the scientific method.
One of the goals of our work is to assist researchers in accessing computing resources without the need for programming or scripting skills. To this effect, we created a toolset able to integrate any command line tool into workflow systems. Out of the box, our toolset supports two widely–used workflow systems, but our modular design allows for seamless additions in order to support further workflow engines.
Recognizing the importance of early and robust workflow design, we also extended a well–established, desktop–based analytics platform that contains more than two thousand tasks (each being a building block for a workflow), allows easy development of new tasks and is able to integrate external command line tools. We developed a converter plug–in that offers a user–friendly mechanism to execute workflows on distributed high–performance computing resources—an exercise that would otherwise require technical skills typically not associated with the average life scientist's profile.
Our converter extension generates virtually identical versions of the same workflows, which can then be executed on more capable computing resources. That is, not only did we leverage the capacity of distributed high–performance resources and the conveniences of a workflow engine designed for personal computers but we also circumvented computing limitations of personal computers and the steep learning curve associated with creating workflows for distributed environments. Our converter extension has immediate applications for researchers and we showcase our results by means of three use cases relevant for life scientists: structural bioinformatics, immunoinformatics and metabolomics
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