Harvesting large-scale grids for software resources

Asterios Katsifodimos; George Pallis; Marios D. Dikaiakos

doi:10.1109/CCGRID.2009.51

Harvesting large-scale grids for software resources

Asterios Katsifodimos^*, George Pallis, Marios D. Dikaiakos

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

4 Citations (Scopus)

Abstract

Grid infrastructures are in operation around the world, federating an impressive collection of computational resources and a wide variety of application software. In this context, it is important to establish advanced software discovery services that could help end-users locate software components suitable to their needs. In this paper, we present the design, architecture and implementation of an open-source keywordbased paradigm for the search of software resources in Grid infrastructures, called Minersoft. A key goal of Minersoft is to annotate automatically all the software resources with keywordrich metadata. Using advanced Information Retrieval techniques, we locate software resources with respect to users queries. Experiments were conducted in EGEE, one of the largest Grid production services currently in operation. Results showed that Minersoft successfully crawled 12.3 million valid files (620 GB size) and sustained, in most sites, high crawling rates.

Original language	English
Title of host publication	2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGRID 2009
Pages	252-259
Number of pages	8
DOIs	https://doi.org/10.1109/CCGRID.2009.51
Publication status	Published - 2009
Externally published	Yes
Event	CCGRID 2009: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid - Shanghai, China Duration: 18 May 2009 → 21 May 2009

Conference

Conference	CCGRID 2009
Country/Territory	China
City	Shanghai
Period	18/05/09 → 21/05/09

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10.1109/CCGRID.2009.51

Cite this

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title = "Harvesting large-scale grids for software resources",

abstract = "Grid infrastructures are in operation around the world, federating an impressive collection of computational resources and a wide variety of application software. In this context, it is important to establish advanced software discovery services that could help end-users locate software components suitable to their needs. In this paper, we present the design, architecture and implementation of an open-source keywordbased paradigm for the search of software resources in Grid infrastructures, called Minersoft. A key goal of Minersoft is to annotate automatically all the software resources with keywordrich metadata. Using advanced Information Retrieval techniques, we locate software resources with respect to users queries. Experiments were conducted in EGEE, one of the largest Grid production services currently in operation. Results showed that Minersoft successfully crawled 12.3 million valid files (620 GB size) and sustained, in most sites, high crawling rates.",

author = "Asterios Katsifodimos and George Pallis and Dikaiakos, {Marios D.}",

year = "2009",

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AU - Pallis, George

AU - Dikaiakos, Marios D.

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AB - Grid infrastructures are in operation around the world, federating an impressive collection of computational resources and a wide variety of application software. In this context, it is important to establish advanced software discovery services that could help end-users locate software components suitable to their needs. In this paper, we present the design, architecture and implementation of an open-source keywordbased paradigm for the search of software resources in Grid infrastructures, called Minersoft. A key goal of Minersoft is to annotate automatically all the software resources with keywordrich metadata. Using advanced Information Retrieval techniques, we locate software resources with respect to users queries. Experiments were conducted in EGEE, one of the largest Grid production services currently in operation. Results showed that Minersoft successfully crawled 12.3 million valid files (620 GB size) and sustained, in most sites, high crawling rates.

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Harvesting large-scale grids for software resources

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