PROV-TE: A Provenance-Driven Diagnostic Framework for Task Eviction in Data Centers

Albatli, A, McKee, D orcid.org/0000-0002-9047-7990, Townend, P et al. (2 more authors) (2017) PROV-TE: A Provenance-Driven Diagnostic Framework for Task Eviction in Data Centers. In: 2017 IEEE Third International Conference on Big Data Computing Service and Applications (IEEE BigDataService 2017). IEEE BigDataService 2017, 06-10 Apr 2017, South San Francisco, California, USA. IEEE , pp. 233-242. ISBN 978-1-5090-6318-5

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Big Data; Data Centers; Cyberinfrastructure; Cloud Computing; Overcommitment; Overload; Provenance; PROV; Simulation; Distributed Systems; Data models; Computational modeling; Google; Analytical models; Distributed databases; Standards
Dates:
  • Published: 12 June 2017
  • Accepted: 14 February 2017
  • Published (online): 12 June 2017
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 24 Feb 2017 12:44
Last Modified: 16 Jan 2018 20:15
Status: Published
Publisher: IEEE
Identification Number: https://doi.org/10.1109/BigDataService.2017.34

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