2006Unpublished venueRequires access

Data Management in Production Grids - Challenges and Techniques

Erwin Laure

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Abstract

Summary form only given. Advances in networking and distributed computing allowed the establishment of production grid infrastructures. Today, large-scale production grid infrastructures such as EGEE in Europe, OSG in the US, and NAREGI in Japan are offering their services to many scientific and industrial applications, from domains as diverse as astronomy, biomedicine, computational chemistry, earth sciences, financial simulations, and high energy physics. Grid infrastructures provide these applications a new means for collaborative research by facilitating the sharing of computational and data resources at an unprecedented scale. The efficient and secure sharing of data resources, which can reach several Tera- to Petabytes in some application domains, is one of the main challenges for grid infrastructures. In this article we discuss the main challenges for data sharing on grid infrastructures, present several techniques that are already established on production grid infrastructures or currently being developed and point out main open research issues. We also present examples of application usage of one of the largest grid infrastructures, EGEE

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What this paper is about

Summary form only given. Advances in networking and distributed computing allowed the establishment of production grid infrastructures. Today, large-scale production grid infrastructures such as EGEE in Europe, OSG in the US, and NAREGI in Japan are offering their services to many scientific and industrial applications, from domains as diverse as astronomy, biomedicine, computational chemistry, earth sciences, financial simulations, and high energy physics. Grid infrastructures provide these applications a new means for collaborative research by facilitating the sharing of computational and data resources at an unprecedented scale. The efficient and secure sharing of data resources, which can reach several Tera- to Petabytes in some application domains, is one of the main challenges for grid infrastructures. In this article we discuss the main challenges for data sharing on grid infrastructures, present several techniques that are already established on production grid infrastructures or currently being developed and point out main open research issues. We also present examples of application usage of one of the largest grid infrastructures, EGEE

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Available abstract

Summary form only given. Advances in networking and distributed computing allowed the establishment of production grid infrastructures. Today, large-scale production grid infrastructures such as EGEE in Europe, OSG in the US, and NAREGI in Japan are offering their services to many scientific and industrial applications, from domains as diverse as astronomy, biomedicine, computational chemistry, earth sciences, financial simulations, and high energy physics. Grid infrastructures provide these applications a new means for collaborative research by facilitating the sharing of computational and data resources at an unprecedented scale. The efficient and secure sharing of data resources, which can reach several Tera- to Petabytes in some application domains, is one of the main challenges for grid infrastructures. In this article we discuss the main challenges for data sharing on grid infrastructures, present several techniques that are already established on production grid infrastructures or currently being developed and point out main open research issues. We also present examples of application usage of one of the largest grid infrastructures, EGEE

Key concepts: Petabyte, Grid computing, Grid, Computer science, Data science, Data grid, Scale (ratio), Production (economics)

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