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 representation, while providing a critical view over the advantages and disadvantages of such a solution.
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