The role of ontologies in autonomic computing systems

Stojanović, Ljiljana; Schneider, Jean-Guy; Maedche, Alexander; Libischer, S.; Studer, Rudi; Lumpp, Th.; Abecker, Andreas; Breiter, Gerd; Dinger, John

doi:10.1147/sj.433.0598

Cited by 82 publications

(37 citation statements)

References 16 publications

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“…It is not the first approach that tries to combine the two elements together [9], [8] but the premiere is its application in the field of business intelligence and data warehouse improvement using business rules.…”

Section: Discussionmentioning

confidence: 99%

“…The ontology representation suits our needs as it provides the solution for two main problems: knowledge unification and knowledge interchange. Works in this area have already been done by [9] and we found this model fully applicable to our system as it covers both knowledge formalization and rule usage. We propose a division of the knowledge aspect into two main categories: static and dynamic.…”

Section: Knowledge Basementioning

confidence: 98%

See 1 more Smart Citation

An Ontology-Based Autonomic System for Improving Data Warehouse Performances

Nicolicin-Georgescu

Benatier

Lehn

et al. 2009

Knowledge-Based and Intelligent Information and Engineering Systems

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Section: Discussionmentioning

confidence: 99%

Section: Knowledge Basementioning

confidence: 98%

An Ontology-Based Autonomic System for Improving Data Warehouse Performances

Nicolicin-Georgescu

Benatier

Lehn

et al. 2009

Knowledge-Based and Intelligent Information and Engineering Systems

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“…In [7], the importance of ontologies in the design and the implementation of autonomic computing systems is described: without an explicit meaning, the resolution of a problem is not possible. As shown in Figure 1, IBM uses the DMTF Common Information Model (CIM) as a reference model to infer properties about distributed systems.…”

Section: Autonomic Network Managementmentioning

confidence: 99%

Ontology-Based Knowledge Representation for Self-governing Systems

Lehtihet

Strassner

Agoulmine

et al. 2006

Lecture Notes in Computer Science

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Abstract. Self-governing systems need a reliable set of semantics and a formal theoretic model in order to facilitate automated reasoning. We present an ontology-based knowledge representation that will use data from information models while preserving the semantics and the taxonomy of existing systems. This will facilitate the decomposition and validation of high level goals by autonomous, self-governing components. Our solution reuses principles and standards from the Semantic Web and the OMG to precisely describe the managed entities and the shared objectives that these entities are trying to achieve by autonomously correlating their behavior. We describe how we created UML2, MOF, OCL and QVT ontologies, and we give a case study using the NGOSS Shared Information and Data model. We also set the requirements for integrating existing information models and domain ontologies into a unique knowledge base.

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“…This would require leveraging techniques from Autonomic Computing [19]. names, may be trademarks or service marks of others.…”

Section: Current Status and Future Workmentioning

confidence: 99%

Towards service orientation in pervasive computing systems

Bellur

Narendra²

2005

International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II

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The emergence of the service-oriented computing paradigm has opened the possibility of using dynamic binding of application requirements to the resources needed to fulfill application tasks. Especially in pervasive computing that is characterized by disconnected operation and mobility, the process of using service specifications and dynamic binding becomes critical. In this paper, we summarize our ongoing work in the area of integrating service orientation into pervasive computing using the notion of specifying service requirements and using these specifications to bind to the available resources dynamically instead of hardwiring them statically. We term these specifications programmable requirements since they can be interpreted at run time to bind to a resource satisfying those specifications. Interestingly this approach also satisfies the basis for two key types of adaptation prevalent in pervasive computing systems -functional and architectural -as we show in this paper.

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The role of ontologies in autonomic computing systems

Cited by 82 publications

References 16 publications

An Ontology-Based Autonomic System for Improving Data Warehouse Performances

An Ontology-Based Autonomic System for Improving Data Warehouse Performances

Ontology-Based Knowledge Representation for Self-governing Systems

Towards service orientation in pervasive computing systems

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