Dynamic Data Replication for Short Time-to-Completion in a Data Grid

Dynamic Data Replication for Short Time-to-Completion in a Data Grid

Abstract

Science collaborations use computer grids to run expensive computational tasks on large data sets. Tasks as jobs across the network demand data and thereby workload management and data allocation to maintain the computational workflow. Data allocation includes data placement with different replication factors (multiplicity) of data. The proposed data replication & allocation model can place multitudes of subsets of a data population in a distributed system, such as a computer cluster or computer grid. A stochastic simulation with a data and computing example from the ATLAS Physics Collaboration shows its potential usability in one of the largest Computing Grids. This paper showcases data allocation with different replica factors and various numbers of subsets to improve the overall situation in a computer network.

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Authors
  • Vamosi, Ralf
  • Schikuta, Erich
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Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
23rd International Conference on Computational Science
Divisions
Workflow Systems and Technology
Subjects
Datenbanken
Event Location
Prague, Czech Republic
Event Type
Conference
Event Dates
3-5 July, 2023
Date
2023
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