The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
BOINC: A System for Public-Resource Computing and Storage
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
Resource Management for Rapid Application Turnaround on Enterprise Desktop Grids
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Future Generation Computer Systems - Special issue: P2P computing and interaction with grids
Biological sequence alignment on the computational grid using the GrADS framework
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
Concurrency and Computation: Practice & Experience
PackageBLAST: an adaptive multi-policy grid service for biological sequence comparison
Proceedings of the 2006 ACM symposium on Applied computing
Bio-STEER: A Semantic Web workflow tool for Grid computing in the life sciences
Future Generation Computer Systems
Scheduling Independent Tasks Sharing Large Data Distributed with BitTorrent
GRID '05 Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing
Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed
International Journal of High Performance Computing Applications
BitDew: a programmable environment for large-scale data management and distribution
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Distributed BLAST in a grid computing context
CompLife'05 Proceedings of the First international conference on Computational Life Sciences
An Enterprise Mashup Integration Service Framework for Clouds
International Journal of Cloud Applications and Computing
An Adaptive Scheduler Framework for Complex Workflow Jobs on Grid Systems
International Journal of Distributed Systems and Technologies
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There exists numerous Grid middleware to develop and execute programs on the computational Grid, but they still require intensive work from their users. BitDew is made to facilitate the usage of large scale Grid with dynamic, heterogeneous, volatile and highly distributed computing resources for applications that require a huge amount of data processing. Data-intensive applications form an important class of applications for the e-Science community which require secure and coordinated access to large datasets, wide-area transfers and broad distribution ofTeraBytes of data while keeping track of multiple data replicas. In genetic biology, gene sequences comparison and analysis are the most basic routines. With the considerable increase of sequences to analyze, we need more and more computing power as well as efficient solution to manage data. In this work, we investigate the advantages of using a new Desktop Grid middleware BitDew, designed for large scale data management.Our contribution is two-fold: firstly, we introduce a data-driven Master/Slave programming model and we present an implementation of BLAST over BitDew following this model, secondly, we present extensive experimental and simulation results which demonstrate the effectiveness and scalability of our approach. We evaluate the benefit of multi-protocol data distribution to achieve remarkable speedups, we report on the ability to cope with highly volatile environment with relative performance degradation, we show the benefit of data replication in Grid with heterogeneous resource performance and we evaluate the combination of data fault tolerance and data replication when computing on volatileresources.