loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Michael Bensch 1 ; Dominik Brugger 1 ; Wolfgang Rosenstiel 1 ; Martin Bogdan 2 ; Wilhelm Spruth 2 and Peter Baeuerle 3

Affiliations: 1 Tübingen University, Germany ; 2 Tübingen University; Leipzig University, Germany ; 3 IBM Germany Development Lab, Germany

ISBN: 978-972-8865-89-4

Keyword(s): Workload management, time series prediction, neural networks, feature selection.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial Applications of Artificial Intelligence ; Methodologies and Methods ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: We present a framework for extraction and prediction of online workload data from a workload manager of a mainframe operating system. To boost overall system performance, the prediction will be incorporated into the workload manager to take preventive action before a bottleneck develops. Model and feature selection automatically create a prediction model based on given training data, thereby keeping the system flexible. We tailor data extraction, preprocessing and training to this specific task, keeping in mind the non-stationarity of business processes. Using error measures suited to our task, we show that our approach is promising. To conclude, we discuss our first results and give an outlook on future work.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.83.32.171

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Bensch M.; Brugger D.; Rosenstiel W.; Bogdan M.; Spruth W.; Baeuerle P. and (2007). SELF-LEARNING PREDICTION SYSTEM FOR OPTIMISATION OF WORKLOAD MANAGEMENT IN A MAINFRAME OPERATING SYSTEM.In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-972-8865-89-4, pages 212-218. DOI: 10.5220/0002392102120218

@conference{iceis07,
author={Michael Bensch and Dominik Brugger and Wolfgang Rosenstiel and Martin Bogdan and Wilhelm Spruth and Peter Baeuerle},
title={SELF-LEARNING PREDICTION SYSTEM FOR OPTIMISATION OF WORKLOAD MANAGEMENT IN A MAINFRAME OPERATING SYSTEM},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2007},
pages={212-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002392102120218},
isbn={978-972-8865-89-4},
}

TY - CONF

JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - SELF-LEARNING PREDICTION SYSTEM FOR OPTIMISATION OF WORKLOAD MANAGEMENT IN A MAINFRAME OPERATING SYSTEM
SN - 978-972-8865-89-4
AU - Bensch, M.
AU - Brugger, D.
AU - Rosenstiel, W.
AU - Bogdan, M.
AU - Spruth, W.
AU - Baeuerle, P.
PY - 2007
SP - 212
EP - 218
DO - 10.5220/0002392102120218

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.