UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods User Group-based Workload Analysis and Modelling

@inproceedings{Song2005UNIVERSITYOD,
  title={UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods User Group-based Workload Analysis and Modelling},
  author={Baiyi Song and Carsten Ernemann and Ramin Yahyapour},
  year={2005}
}
Knowledge about the workload is an important aspect for scheduling of resources as parallel computers or Grid components. As the scheduling quality highly depends on the characteristics of the workload running on such resources, a representative workload model is significant for performance evaluation. Previous approaches on workload modelling mainly focused on methods that use statistical distributions to fit the overall workload characteristics. Therefore, the individual association and… CONTINUE READING

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