A taxonomy of Data Grids for distributed data sharing, management, and processing

By Srikumar Venugopal, Rajkumar Buyya, Kotagiri Ramamohanarao. CSUR, 2005

379 citations recorded by the source corpus.

Data Grids have been adopted as the next generation platform by many 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 article, 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.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/ac3681e5a6b1c894209082b2f3e287021517b7c4

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In Computer Networks and Communications

Citations in the corpus

A data placement strategy in scientific cloud workflows (2010, neutral): “Data grids primarily deal with providing services and an infrastructure for distributed data-intensive applications that need to access, transfer, and modify massivedatasetsstoredindistributedstorageresources[31].”
Big Data computing and clouds: Trends and future directions (2013, methodology): “The same approach of exploring data locality was explored previously in scientific workflows [39] and in Data Grids [40] 3http://aws.amazon.com/s3/ 4http://www.nirvanix.com 5http://swift.openstack.org 6http://www.windowsazure.com/en-US/services/data-management/ In the context of Big Data analytics, ”