A configuration management approach for large workflow management systems

Schuster, H.; Neeb, Jens; Schamburger, Ralf

doi:10.1145/295665.295686

Cited by 20 publications

(14 citation statements)

References 7 publications

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“…The work reported in [2,3] presents several types of distributed WFMS architectures and discusses the influence of different load distribution methods on the network and workflow-server load, mostly using simulations. [20] presents heuristics for the allocation of workflow-type and workflow-instance data onto servers. Mechanisms for enhanced WFMS availability by replicating state data on a standby backup server have been studied in [9,14].…”

Section: Related Workmentioning

confidence: 99%

Workflow management with service quality guarantees

Gillmann¹,

Weikum²,

Wonner³

2002

Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data - SIGMOD '02

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Workflow management systems (WFMS) that are geared for the orchestration of business processes across multiple organizations are complex distributed systems: they consist of multiple workflow engines, application servers, and communication middleware servers such as ORBs, where each of these server types can be replicated on multiple computers for scalability and availability. Finding an appropriate system configuration with guaranteed application-specific quality of service in terms of throughput, response time, and tolerable downtime is a major challenge for human system administrators. This paper presents a tool that largely automates the task of configuring a distributed WFMS. Based on a suite of mathematical models, the tool derives the necessary degrees of replication for the various server types in order to meet specified goals for performance and availability as well as "performability" when service is degraded due to outages of individual servers. The paper describes the configuration tool, with emphasis on how to capture the load behavior of workflows in a realistic manner. We also present extensive experiments that evaluate the accuracy of the tool's underlying models and demonstrate the practical feasibility of automating the task of configuring a distributed WFMS. The experiments use a detailed simulation which in turn has been validated through measurements with the Mentor-lite prototype system.

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Section: Related Workmentioning

confidence: 99%

Workflow management with service quality guarantees

Gillmann¹,

Weikum²,

Wonner³

2002

Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data - SIGMOD '02

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“…In this distributed variant of the ADEPT system, we allow WF designers to subdivide a WF schema into several partitions which are then controlled "piecewise" by different WF servers in order to obtain favorable communication behavior. Note that similar approaches have been discussed in literature (Alonso, 1995;Casati, 1996;Cichocki, 2000;Dogac, 1997;Gronemann, 1999;Guth, 1998;Kochut, 2003;Muth, 1998;Schuster, 1999;Sheth, 1997;Weske, 1999).…”

Section: Problem Statementmentioning

confidence: 76%

“…Some of them assign a WF instance (as a whole) always to the same WF server. Examples include Exotica/Cluster (Alonso, 1994) and MOBILE (Jablonski, 1997); the latter approach was extended in (Schuster, 1999). Comparable to our techniques, the approaches provided by MENTOR (Muth, 1998) and WIDE (Casati, 1996) select the WF server for a WF activity next to its potential actors.…”

Section: Discussionmentioning

confidence: 99%

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Flexibility for Distributed Workflows

Reichert

Bauer

Dadam

2013

Enterprise Resource Planning

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This chapter shows how flexibility can be realized for distributed workflows. The capability to dynamically adapt workflow instances during runtime (e.g., to add, delete or move activities) constitutes a fundamental challenge for any workflow management system (WfMS). While there has been significant research on ad-hoc workflow changes and on related correctness issues, there exists only little work on how to provide respective runtime flexibility in an enterprise-wide context as well. Here, scalability at the presence of high loads constitutes an essential requirement, often necessitating distributed (i.e., piecewise) control of a workflow instance by different workflow servers, which should be as independent from each other as possible. This chapter presents advanced concepts and techniques for enabling ad-hoc workflow changes in a distributed WfMS as well. Our focus is on minimizing the communication costs among workflow servers, while ensuring a correct execution behavior as well as correctness of ad-hoc workflow changes at any time.

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“…In [SNS99] wurde der MOBILE-Ansatz noch erweitert. Beim Start eines (Sub-)WF, also zur Laufzeit, wird entschieden, von welchem WF-Server dieser kontrolliert werden soll.…”

Section: Server Sind Nahe Bei Den Bearbeiternunclassified

Verteilungsmodelle für Workflow-Management-Systeme – Klassifikation und Simulation

Bauer

Dadam

1999

Informatik Forsch Entw

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Zusammenfassung.In unternehmensweiten Workflow-Management-Systemen (WfMS) kann die von der WF-Engine zu bewältigende Last sehr groß werden. Außerdem werden hohe Anforderungen an die Verfügbarkeit eines solchen Systems gestellt. Deshalb wurden in der Literatur zahlreiche Architekturen für skalierbare WfMS vorgeschlagen, die auf unterschiedlichen Verteilungsmodellen für die WF-Engine basieren. Im vorliegenden Beitrag werden diese Verteilungsmodelle analysiert, verglichen und klassifiziert. Aufbauend auf diese Klassifikation wird für zwei Beispielszenarien die bei den verschiedenen Verteilungsmodellen entstehende Last simuliert und verglichen.Abstract. In enterprise-wide workflow management systems (WfMS) the workflow engine may have to cope with a very high load. In addition, the availability of such a system must be high. Many architectures for scalable WfMS have been proposed in the literature, which are based on different distribution models of the workflow engine. These distribution models are analyzed, compared, and classified. Based on this classification, two example scenarios are used to simulate and compare the load resulting for the different distribution models.

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A configuration management approach for large workflow management systems

Cited by 20 publications

References 7 publications

Workflow management with service quality guarantees

Workflow management with service quality guarantees

Flexibility for Distributed Workflows

Verteilungsmodelle für Workflow-Management-Systeme – Klassifikation und Simulation

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