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BitDew: a programmable environment for large-scale data management and distribution
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Proceedings of the 2008 ACM/IEEE conference on Supercomputing - Volume 00 table of contents
Austin, Texas
SECTION: Papers table of contents
Article No. 45  
Year of Publication: 2008
ISBN:978-1-4244-2835-9
Authors
Gilles Fedak  Univ Paris-Sud, CNRS, Orsay
Haiwu He  Univ Paris-Sud, CNRS, Orsay
Franck Cappello  Univ Paris-Sud, CNRS, Orsay
Publisher
IEEE Press  Piscataway, NJ, USA
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ABSTRACT

Desktop Grids use the computing, network and storage resources from idle desktop PC's distributed over multiple-LAN's or the Internet to compute a large variety of resource-demanding distributed applications. While these applications need to access, compute, store and circulate large volumes of data, little attention has been paid to data management in such large-scale, dynamic, heterogeneous, volatile and highly distributed Grids. In most cases, data management relies on ad-hoc solutions, and providing a general approach is still a challenging issue.

To address this problem, we propose the BitDew framework, a programmable environment for automatic and transparent data management on computational Desktop Grids. This paper describes the BitDew programming interface, its architecture, and the performance evaluation of its runtime components. BitDew relies on a specific set of meta-data to drive key data management operations, namely life cycle, distribution, placement, replication and fault-tolerance with a high level of abstraction. The Bitdew runtime environment is a flexible distributed service architecture that integrates modular P2P components such as DHT's for a distributed data catalog and collaborative transport protocols for data distribution. Through several examples, we describe how application programmers and Bitdew users can exploit Bitdew's features. The performance evaluation demonstrates that the high level of abstraction and transparency is obtained with a reasonable overhead, while offering the benefit of scalability, performance and fault tolerance with little programming cost.


REFERENCES

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Collaborative Colleagues:
Gilles Fedak: colleagues
Haiwu He: colleagues
Franck Cappello: colleagues