A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Distributed authorization in loosely coupled data federation

The underlying data model of many integrated information systems is a collection of inter-operable and autonomous database systems, namely, a loosely coupled data federation. A challenging security issue in designing such a data federation is to ensure the integrity and confidentiality of data stored in remote databases through distributed authorization of users. Existing solutions in centralized databases are not directly applicable here due to the lack of a centralized authority, and most solutions designed for outsourced databases cannot easily support frequent updates essential to a data federation. In this thesis, we provide a solution in three steps. First, we devise an architecture to support fully distributed, fine-grained, and data-dependent authorization in loosely coupled data federations. For this purpose, we adapt the integrity-lock architecture originally designed for multilevel secure databases to data federations. Second, we propose an integrity mechanism to detect, localize, and verify updates of data stored in remote databases while reducing communication overhead and limiting the impact of unauthorized updates. We realize the mechanism as a three-stage procedure based on a grid of Merkle Hash Trees built on relational tables. Third, we present a confidentiality mechanism to control remote users' accesses to sensitive data while allowing authorization policies to be frequently updated. We achieve this objective through a new over-encryption scheme based on secret sharing. Finally, we evaluate the proposed architecture and mechanisms through experiments