Data Allocation Service ADAS for the Data Rebalancing of ATLAS

Data Allocation Service ADAS for the Data Rebalancing of ATLAS

Abstract

The distributed data management system Rucio manages all data of the ATLAS collaboration across the grid. Automation, such as data replication and data rebalancing are important to ensure proper operation and execution of the scientific workflow. In this proceedings, a new data allocation grid service based on machine learning is proposed. This learning agent takes subsets of the global datasets and proposes a better allocation based on the imposed cost metric, such as waiting time in the workflow. As a service, it can be modularized and can run independently of the existing rebalancing and replication mechanisms. Furthermore, it collects data from other services and learns better allocation while running in the background. Apart from the user selecting datasets, other data services may consult this meta-heuristic service for improved data placement. Network and storage utilization is also taken into account.

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Authors
  • Vamosi, Ralf
  • Lassnig, Mario
  • Schikuta, Erich
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Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
23rd International Conference on Computing in High Energy and Nuclear Physics
Divisions
Workflow Systems and Technology
Subjects
Angewandte Informatik
Event Location
Sofia, Bulgaria
Event Type
Conference
Event Dates
9-13 Jul 2018
Series Name
EPJ Web of Conferences 214
Date
9 July 2018
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