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A goal in cloud computing is to allocate (and thus pay for) only those cloud resources that are truly needed. To date, cloud practitioners have pursued schedule-based (e.g., time-of-day) and rule-based mechanisms to attempt to automate this matching between computing requirements and computing resources. However, most of these "auto-scaling" mechanisms only(More)
1 1 This paper has been revised and extended from the authors' previous work [23][24][25]. ABSTRACT Ontology mapping seeks to find semantic correspondences between similar elements of different ontologies. It is a key challenge to achieve semantic interoperability in building the Semantic Web. This paper proposes a new generic and adaptive ontology mapping(More)
Introduction Ontology matching 1 is a key interoperability enabler for the Semantic Web, as well as a useful tactic in some classical data integration tasks dealing with the semantic heterogeneity problem. It takes ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of these(More)
A significant open issue in cloud computing is performance. Few, if any, cloud providers or technologies offer quantitative performance guarantees. Regardless of the potential advantages of the cloud in comparison to enterprise-deployed applications, cloud infrastructures may ultimately fail if deployed applications cannot predictably meet behavioral(More)
E-Learning is a fast, just-in-time, and non-linear learning process, which is now widely applied in distributed and dynamic environments such as on the World Wide Web. However, it also poses three challenges to the systems that support e-learning. This paper present our on-going effort to develop an ontology-based framework for e-learning systems, which(More)
Ontology has been used widely to help finding relevant information among distributed and heterogeneous sources. Given that no universal ontology exists for the WWW, ontology mapping attracts many researchers' interest in various areas. In this paper we propose a new generic ontology mapping approach based on profile propagation and information retrieval(More)