Data transformation services over grids with real-time bound constraints

Abstract

Data and Knowledge Grids represent emerging and attracting application scenarios for Grid Computing, and pose novel and previously-unrecognized challenges to the research community. Basically, Data and Knowledge Grids found on high-performance Grid infrastructures and add to the latter meaningful data- and knowledge-oriented abstractions and metaphors that perfectly marry with innovative requirements of modern complex Intelligent Information Systems. To this end, service-oriented architectures and paradigms are the most popular ones for Grids, and on the whole represent an active and widely-recognized area of Grid Computing research. In this paper, we introduce the so-called Grid-based RTSOA frameworks, which essentially combine Grid Computing with real-time service management and execution paradigms, and put the basis for novel research perspectives in data-intensive e-science Grid applications with real-time bound constraints. This novel framework is then specialized to the particular context of Data Transformation services over Grids, which play a relevant role for both Data and Knowledge Grids. Finally, we complete the main contribution of the paper with a rigorous theoretical model for efficiently supporting Grid-based RTSOA frameworks, with particular emphasis to the context of Data Transformation services over Grids, along with its preliminary experimental assessment. © 2008 Springer Berlin Heidelberg.