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Towards autonomic workflow management systems
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Source IBM Centre for Advanced Studies Conference archive
Proceedings of the 2006 conference of the Center for Advanced Studies on Collaborative research table of contents
Toronto, Ontario, Canada
SESSION: M table of contents
Article No. 34  
Year of Publication: 2006
Authors
Markus Strohmaier  University of Toronto
Eric Yu  University of Toronto
Sponsors
: IBM Toronto Lab
: CAS
Publisher
ACM  New York, NY, USA
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ABSTRACT

In a world of dynamic and discontinuous change, systems constantly need to adapt to new conditions so that they can survive and flourish in their environment. Autonomic computing emerged as a research field that takes up this challenge and aims to build systems that are capable of adapting automatically to dynamically changing environments (Self-configuring), discovering, diagnosing and reacting to disruptions (Self-healing), monitoring and tuning resources automatically (Self-optimizing) and anticipating, detecting, identifying and protecting themselves from attacks (Self-protecting) [3]. A major application area for autonomic computing is intended to be system administration, aiming to free system administrators from the details of system operation and maintenance [8], improving robustness of systems and decreasing total cost of ownership. However, the vision of autonomic computing does not need to be restricted to the area of system administration. For example, much research has been done in the area of process-aware information systems [2] such as Workflow Management, Enterprise Resource Planning, Business-to-Business and Customer Relationship systems to effectively and efficiently deal with change on different levels and scales. Frequent questions in these domains include: How can changes to workflows be accommodated? How can flexibility and adaptability of running workflow instances be increased? How can workflow management systems themselves optimize workflow definitions? The type of questions raised here seems to address issues that are similarly addressed by research in autonomic computing, where dealing with change represents a major concern. However, little research has been done on the intersection between these two domains [4]. Based on this observation, this contribution aims to tackle the question: "Can the principles of autonomic computing be applied to workflow management - and if so, how?"


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
IBM WebSphere MQ Workflow Software, http://www.306.ibm.com/software/integration/wmqwf/, last accessed on May 31, 2006.
 
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D. Hollingsworth. Workflow Management Coalition (WfMC) - The Workflow Reference Model. Technical report, Workflow Management Coalition, Jan 1995.
 
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R. Mueller. Event-Oriented Dynamic Adaptation of Workflows: Model, Architecture and Implementation. PhD thesis, University of Leipzig, 2002.
 
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Open Source. ProM - Framework for Process Mining. http://sourceforge.net/projects/prom, last accessed on May 31st 2006.
 
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W. M. P. van der Aalst, C. Günther, J. Recker, and M. Reichert. Using Process Mining to Analyze and Improve Process Flexibility. In Proceedings of CAISE'06 - The 18th Conference on Advanced Information Systems Engineering, 2006.

Collaborative Colleagues:
Markus Strohmaier: colleagues
Eric Yu: colleagues