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Open AccessJournal ArticleDOI

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

TLDR
In this article, 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.
Abstract
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.

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Journal ArticleDOI

Big Data computing and clouds

TL;DR: This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications, and identifies possible gaps in technology and provides recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions.
Journal ArticleDOI

A method for taxonomy development and its application in information systems

TL;DR: The purpose of this paper is to present a method for taxonomy development that can be used in IS and demonstrates the efficacy of the method by developing a taxonomy in a domain in IS.
Book

Handbook of Cloud Computing

TL;DR: This handbook presents the systems, tools, and services of the leading providers of cloud computing; including Google, Yahoo, Amazon, IBM, and Microsoft.
Journal ArticleDOI

A data placement strategy in scientific cloud workflows

TL;DR: A matrix based k-means clustering strategy for data placement in scientific cloud workflows that dynamically clusters newly generated datasets to the most appropriate data centres-based on dependencies-during the runtime stage is proposed.
References
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Journal ArticleDOI

A survey on sensor networks

TL;DR: The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections.
Proceedings ArticleDOI

Chord: A scalable peer-to-peer lookup service for internet applications

TL;DR: Results from theoretical analysis, simulations, and experiments show that Chord is scalable, with communication cost and the state maintained by each node scaling logarithmically with the number of Chord nodes.
Book

The Grid 2: Blueprint for a New Computing Infrastructure

TL;DR: The Globus Toolkit as discussed by the authors is a toolkit for high-throughput resource management for distributed supercomputing applications, focusing on real-time wide-distributed instrumentation systems.
Book ChapterDOI

Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems

TL;DR: Pastry as mentioned in this paper is a scalable, distributed object location and routing substrate for wide-area peer-to-peer ap- plications, which performs application-level routing and object location in a po- tentially very large overlay network of nodes connected via the Internet.
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