Abstract.To realize real-time information sharing in generic platforms, it is especially important to support dynamic message structure changes. For the case of IDL, it is necessary to rewrite applications to change data sample structures. In this paper, we propose a dynamic reconfiguration scheme of data sample structures for DDS. Instead of using IDL, which is the static data sample structure model of DDS, we use a self describing model using data sample schema, as a dynamic data sample structure model to support dynamic reconfiguration of data sample structures. We also propose a data propagation model to provide data persistency in distributed environments. We guarantee persistency by transferring data samples through relay nodes to the receiving nodes, which have not participated in the data distribution network at the data sample distribution time. The proposed schemes can be utilized to support data sample structure changes during operation time and to provide data persistency in various environments, such as real-time enterprise environments and connection-less internet environments.
Ontology is a description of the concepts and relationships that can exist for an agent or a community of agents. Ontologies are a key enabling technology for the Semantic Web. Previously, ontologies have been built manually by knowledge engineers using ontology editors. In this paper, we propose a semiautomatic ontology construction scheme for visual media data brokers and providers. We apply data mining techniques on sets of image data groups to determine general term relationships and utilize WordNet to determine semantic relationships between terms. Even though our research has been started for visual media data retrieval, the proposed scheme can be also applied to other problem domains.
The architecture named the GALIS is a cluster-based distributed computing system architecture which has been devised to efficiently handle a large volume of LBS application data. In this paper, we propose a distributed k-NN query processing scheme for moving objects on multiple computing nodes, each of which keeps records relevant to a different geographical zone. We also propose a hybrid k-NN scheme, which utilizes range queries instead of k-NN queries for the neighboring overlapped nodes, thus resulting in 30% reduction of query processing cost. Through some experiments, we show the efficiency of hybrid k-NN scheme over naïve k-NN scheme.
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