This paper addresses the problem of efficiently storing and accessing massive data blocks in a large-scale distributed environment, while providing efficient fine-grain access to data subsets. This issue is crucial in the context of applications in the field of databases, data mining and multimedia. We propose a data sharing service based on distributed, RAM-based storage of data, while leveraging a DHT-based, natively parallel metadata management scheme. As opposed to the most commonly used grid storage infrastructures that provide mechanisms for explicit data localization and transfer, we provide a transparent access model, where data are accessed through global identifiers. Our proposal has been validated through a prototype implementation whose preliminary evaluation on the Grid'5000 testbed provides promising results. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Nicolae, B., Antoniu, G., & Bougé, L. (2008). Distributed management of massive data: An efficient fine-grain data access scheme. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5336 LNCS, pp. 532–543). https://doi.org/10.1007/978-3-540-92859-1_47
Mendeley helps you to discover research relevant for your work.