Publikationsserver der Universitätsbibliothek Marburg

Titel:Supporting Quality of Service in Scientific Workflows
Autor:Dörnemann, Tim
Weitere Beteiligte: Freisleben, Bernd (Prof. Dr.)
Veröffentlicht:2012
URI:https://archiv.ub.uni-marburg.de/diss/z2012/0079
DOI: https://doi.org/10.17192/z2012.0079
URN: urn:nbn:de:hebis:04-z2012-00790
DDC: Informatik
Titel(trans.):Supporting Quality of Service in Scientific Workflows
Publikationsdatum:2012-06-14
Lizenz:https://rightsstatements.org/vocab/InC-NC/1.0/

Dokument

Schlagwörter:
Cloud Computing, Workflow, Business Process Execution Language, Cloud Computing, Business Process Execution Language, Prozessmanagement, Fehler, Scheduling, Grid Computing, Grid Computing, High Performance Computing, Web Services, Hochleistungsrechnen, Web Services

Summary:
While workflow management systems have been utilized in enterprises to support businesses for almost two decades, the use of workflows in scientific environments was fairly uncommon until recently. Nowadays, scientists use workflow systems to conduct scientific experiments, simulations, and distributed computations. However, most scientific workflow management systems have not been built using existing workflow technology; rather they have been designed and developed from scratch. Due to the lack of generality of early scientific workflow systems, many domain-specific workflow systems have been developed. Generally speaking, those domain-specific approaches lack common acceptance and tool support and offer lower robustness compared to business workflow systems. In this thesis, the use of the industry standard BPEL, a workflow language for modeling business processes, is proposed for the modeling and the execution of scientific workflows. Due to the widespread use of BPEL in enterprises, a number of stable and mature software products exist. The language is expressive (Turingcomplete) and not restricted to specific applications. BPEL is well suited for the modeling of scientific workflows, but existing implementations of the standard lack important features that are necessary for the execution of scientific workflows. This work presents components that extend an existing implementation of the BPEL standard and eliminate the identified weaknesses. The components thus provide the technical basis for use of BPEL in academia. The particular focus is on so-called non-functional (Quality of Service) requirements. These requirements include scalability, reliability (fault tolerance), data security, and cost (of executing a workflow). From a technical perspective, the workflow system must be able to interface with the middleware systems that are commonly used by the scientific workflow community to allow access to heterogeneous, distributed resources (especially Grid and Cloud resources). The major components cover exactly these requirements: Cloud Resource Provisioner Scalability of the workflow system is achieved by automatically adding additional (Cloud) resources to the workflow system’s resource pool when the workflow system is heavily loaded. Fault Tolerance Module High reliability is achieved via continuous monitoring of workflow execution and corrective interventions, such as re-execution of a failed workflow step or replacement of the faulty resource. Cost Aware Data Flow Aware Scheduler The majority of scientific workflow systems only take the performance and utilization of resources for the execution of workflow steps into account when making scheduling decisions. The presented workflow system goes beyond that. By defining preference values for the weighting of costs and the anticipated workflow execution time, workflow users may influence the resource selection process. The developed multiobjective scheduling algorithm respects the defined weighting and makes both efficient and advantageous decisions using a heuristic approach. Security Extensions Because it supports various encryption, signature and authentication mechanisms (e.g., Grid Security Infrastructure), the workflow system guarantees data security in the transfer of workflow data. Furthermore, this work identifies the need to equip workflow developers with workflow modeling tools that can be used intuitively. This dissertation presents two modeling tools that support users with different needs. The first tool, DAVO (domain-adaptable, Visual BPEL Orchestrator), operates at a low level of abstraction and allows users with knowledge of BPEL to use the full extent of the language. DAVO is a software that offers extensibility and customizability for different application domains. These features are used in the implementation of the second tool, SimpleBPEL Composer. SimpleBPEL is aimed at users with little or no background in computer science and allows for quick and intuitive development of BPEL workflows based on predefined components.

Zusammenfassung:
Während Unternehmen bereits seit zwei Jahrzehnten auf Workflow-Systeme zur Modellierung und Ausführung von komplexen, IT-gestützten Arbeitsabläufen (Geschäftsprozesse) zurückgreifen, kommen derartige Technologien im wissenschaftlichen Umfeld erst seit wenigen Jahren verbreitet zum Einsatz. Seitdem wurde von Wissenschaftlern eine Reihe von Workflow-Systemen entwickelt, mit deren Hilfe komplexe Experimente modelliert und ausgeführt werden können. Dabei handelt es sich meist um rechenintensive, auf verteilten Rechnersystemen berechnete, Simulationen. Die bisher entwickelten wissenschaftlichen Workflow-Systeme sind in der Regel stark auf die Besonderheiten der Anwendungsfälle der jeweiligen Wissenschaftsdomäne ausgerichtet und können daher in anderen Anwendungsgebieten schlecht oder gar nicht eingesetzt werden. Ausserdem wurden die Workflow-Systeme oft sehr eng an bestimmte Technologien (z.B. eine Grid-Middleware) gekoppelt und sind daher ebenfalls in ihrer Wiederverwendbarkeit eingeschränkt. In dieser Doktorarbeit wird daher vorgeschlagen, den Industriestandard BPEL, eine Workflow-Sprache zur Modellierung von Geschäftsprozessen, zur Modellierung und Ausführung von wissenschaftlichen Workflows zu verwenden. Durch die grosse Verbreitung von BPEL im kommerziellen Umfeld existiert eine Reihe von stabilen und ausgereiften Software-Produkten, die auch im wissenschaftlichen Umfeld eingesetzt werden könnten. Weiterhin ist die Sprache sehr ausdrucksstark (Turing-vollständig) und nicht auf bestimmte Anwendungsbereiche eingeschränkt. Der Standard wird zunächst auf seine Anwendbarkeit zur Modellierung von wissenschaftlichen Workflows hin untersucht. Während BPEL sehr gut zur Modellierung geeignet ist, fehlen existierenden Implementierungen des Standards wichtige Fähigkeiten, die zur Ausführung von wissenschaftlichen Workflows notwendig sind. Diese Arbeit präsentiert daher Komponenten, die eine existierende Implementierung des BPEL-Standards erweitern und die identifizierten Schwachstellen beseitigen. Sie stellen somit die technische Grundlage zur Verwendung von BPEL im wissenschaftlichen Umfeld dar. Der besondere Fokus liegt dabei auf sog. nichtfunktionalen Anforderungen bezüglich der Dienstgüte (Quality of Service). Darunter sind insbesondere Anforderungen wie Skalierbarkeit, Zuverlässigkeit (Fehlertoleranz), Datensicherheit und Kosten (der Ausführung eines Workflows) zu verstehen. Aus technischer Sicht muss das Workflow-System gängige Middleware-Systeme unterstützen, um den Zugriff auf verschiedenartige, verteilte Ressourcen (insbesondere Grid und Cloud-Ressourcen) zu ermöglichen. Die entwickelten Hauptkomponenten decken genau diese Anforderungen ab: Cloud Resource Provisioner Skalierbarkeit wird durch die automatisierte Hinzunahme von weiteren (Cloud) Ressourcen erreicht, wenn das Workflow-System stark ausgelastet ist. Fault Tolerance Module Hohe Zuverlässigkeit wird durch kontinuierliche Überwachung der Workflow-Ausführung und korrigierender Eingriffe, wie erneute Ausführung eines fehlgeschlagenenWorkflow-Schritts oder Austausch der fehlerhaften Ressource, erreicht. Cost And Data Flow Aware Scheduler Viele Workflow-Systeme berücksichtigung bei der Auswahl von Ressourcen zur Ausührung der einzelnen Workflow- Schritte nur die Leistungsfähigkeit und Auslastung in Frage kommender Ressourcen. Das hier präsentierte System geht darüber hinaus: Der Workflow- Nutzer kann durch Angabe von Präferenzwerten entscheiden, welchen Einfluss Kosten und zu erwartende Workflow-Ausführungsdauer auf die Auswahl von Ressourcen haben soll. Der entwickelte multikriterielle Scheduling-Algorithmus beachtet die definierte Gewichtung und trifft durch den Einsatz eines heuristischen Verfahrens schnelle und gute Auswahlentscheidungen. Security Extensions Durch die Unterstützung verschiedener Verschlüsselungs-, Signatur- und Authentisierungsmechanismen (insbesondere Grid Security Infrastructure) wird Datensicherheit bei der Übertragung von Workflow-Daten garantiert. Weiterhin identifiziert diese Arbeit die Notwendigkeit, Workflow-Entwicklern intuitiv bedienbare Werkzeuge zur Workflow-Modellierung zur Verfügung zu stellen. Es werden zwei Modellierungswerkzeuge präsentiert, die Anwender mit unterschiedlichen Bedürfnissen unterstützen. DAVO (Domain-adaptable, Visual BPEL Orchestrator) arbeitet auf einem niedrigen Abstraktionsniveau und erlaubt es Anwendern mit Kenntnissen in BPEL, den vollen Umfang der Sprache zu nutzen. DAVO ist eine Software mit umfangreichen Erweiterungs- und Anpassungsmöglichkeiten. Diese Fähigkeiten werden bei der Umsetzung des zweiten Werkzeugs, SimpleBPEL Composer, genutzt. SimpleBPEL richtet sich an Anwender mit geringen Informatik- Kenntnissen und ermöglicht die schnelle und intuitive Entwicklung von BPELWorkflows auf Basis vordefinierter Bausteine.

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