Abstract
Euro-Par Topic 5 addresses data management issues in parallel and distributed computing. Advances in data management (storage, access, querying, retrieval, mining) are inherent to current and future information systems. Today, accessing large volumes of information is a reality: Data-intensive applications enable huge user communities to transparently access multiple pre-existing autonomous, distributed and heterogeneous resources (data, documents, images, services, etc.). Data management solutions need efficient techniques for exploiting and mining large datasets available in clusters, peer to peer and Grid architectures. Parallel and distributed file systems, databases, data warehouses, and digital libraries are a key element for achieving scalable, efficient systems that will cost-effectively manage and extract data from huge amounts of highly distributed and heterogeneous digital data repositories.
Chapter PDF
Similar content being viewed by others
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Szalay, A., Hiemstra, D., Kemper, A., Prieto, M. (2009). Introduction. In: Sips, H., Epema, D., Lin, HX. (eds) Euro-Par 2009 Parallel Processing. Euro-Par 2009. Lecture Notes in Computer Science, vol 5704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03869-3_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-03869-3_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03868-6
Online ISBN: 978-3-642-03869-3
eBook Packages: Computer ScienceComputer Science (R0)