Self-describing and data propagation model for data distribution service

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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. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Lee, C., Hwang, J., Lee, J., Ahn, C., Suh, B., Shin, D. H., … Kim, D. H. (2008). Self-describing and data propagation model for data distribution service. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5287 LNCS, pp. 102–113). https://doi.org/10.1007/978-3-540-87785-1_10

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