loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Vlad Nicolicin-Georgescu 1 ; Vincent Benatier 1 ; Remi Lehn 2 and Henri Briand 2

Affiliations: 1 SP2 Solutions, France ; 2 LINA CNRS 6241, COD Team, Ecole Polytechnique de l’Unviersité de Nantes, France

ISBN: 978-989-8425-06-5

Keyword(s): Autonomic Computing, Decision Support System, Data Warehouse, Ontology.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Cloud Computing ; Data Engineering ; Data Warehouses and OLAP ; Databases and Information Systems Integration ; Enterprise Information Systems ; Health Information Systems ; Informatics in Control, Automation and Robotics ; Information Systems Analysis and Specification ; Intelligent Control Systems and Optimization ; Knowledge Engineering ; Knowledge Engineering and Ontology Development ; Knowledge Management ; Knowledge-Based Systems ; Knowledge-Based Systems Applications ; Ontologies and the Semantic Web ; Ontology Engineering ; Semantic Web Technologies ; Services Science ; Society, e-Business and e-Government ; Software Agents and Internet Computing ; Software Engineering ; Symbolic Systems ; Web Information Systems and Technologies

Abstract: Complexity is the biggest challenge in managing information systems today, because of the continuous growth in data and information. As decision experts, we are faced with the problems generated by managing Decision Support Systems, one of which is the efficient allocation of shared resources. In this paper, we propose a solution for improving the allocation of shared resources between groups of data warehouses within a decision support system, with the Service Levels Agreements and Quality of Service as performance objectives. We base our proposal on the notions of autonomic computing, by challenging the traditional way of autonomic systems and by taking into consideration decision support systems’ special characteristics such as usage discontinuity or service level specifications. To this end, we propose the usage of specific heuristics for the autonomic self-improvement and integrate aspects of semantic web and ontology engineering as information source for knowledge base represent ation, while providing a critical view over the advantages and disadvantages of such a solution. (More)

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 35.168.111.191

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:
Nicolicin-Georgescu V.; Benatier V.; Lehn R.; Briand H. and (2010). ONTOLOGY-BASED AUTONOMIC COMPUTING FOR RESOURCE SHARING BETWEEN DATA WAREHOUSES IN DECISION SUPPORT SYSTEMS.In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-06-5, pages 199-206. DOI: 10.5220/0002895501990206

@conference{iceis10,
author={Vlad Nicolicin{-}Georgescu and Vincent Benatier and Remi Lehn and Henri Briand},
title={ONTOLOGY-BASED AUTONOMIC COMPUTING FOR RESOURCE SHARING BETWEEN DATA WAREHOUSES IN DECISION SUPPORT SYSTEMS},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2010},
pages={199-206},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002895501990206},
isbn={978-989-8425-06-5},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - ONTOLOGY-BASED AUTONOMIC COMPUTING FOR RESOURCE SHARING BETWEEN DATA WAREHOUSES IN DECISION SUPPORT SYSTEMS
SN - 978-989-8425-06-5
AU - Nicolicin-Georgescu, V.
AU - Benatier, V.
AU - Lehn, R.
AU - Briand, H.
PY - 2010
SP - 199
EP - 206
DO - 10.5220/0002895501990206

Login or register to post comments.

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