Quartz: a tool for tuning parallel program performance
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
The action workflow approach to workflow management technology
CSCW '92 Proceedings of the 1992 ACM conference on Computer-supported cooperative work
P.S. to operating systems
Process innovation: reengineering work through information technology
Process innovation: reengineering work through information technology
Analyzing and re-engineering business processes using simulation
WSC '94 Proceedings of the 26th conference on Winter simulation
Artificial Intelligence
IPS-2: The Second Generation of a Parallel Program Measurement System
IEEE Transactions on Parallel and Distributed Systems
WorkWeb system—multi-workflow management with a multi-agent system
GROUP '97 Proceedings of the international ACM SIGGROUP conference on Supporting group work: the integration challenge
Performance Equivalent Analysis of Workflow Systems Based on Stochastic Petri Net Models
EDCIS '02 Proceedings of the First International Conference on Engineering and Deployment of Cooperative Information Systems
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We present a framework that enables reengineers to build a base of performance improvement knowledge that can be used to automatically improve workflow performance. Automatic improvement of workflow performance involves modification of a business information system such that the predicted performance of its business workflows satisfies a performance goal. The number of possible modification options is very large, so a significant body of knowledge is needed to choose among them. We demonstrate, using a simple example, the requirements for the types of knowledge necessary in a automatic improvement framework. We define a knowledge model for representing these types of knowledge. We use the model to provide the framework with a body of domain-independent performance improvement knowledge. We then describe how the framework enables reengineers to provide additional performance improvement knowledge to the model and how the framework utilizes that knowledge to automatically improve workflow performance to meet the performance goal.