Timely Long Tail Identification through Agent Based Monitoring and Analytics

Garraghan, PM, Ouyang, X, Townend, P et al. (1 more author) (2015) Timely Long Tail Identification through Agent Based Monitoring and Analytics. In: Real-Time Distributed Computing (ISORC), 2015 IEEE 18th International Symposium on. IEEE 18th International Symposium on Real-Time Distributed Computing (ISORC), 13-17 Apr 2015, Auckland, New Zealand. Institute of Electrical and Electronics Engineers , 19 - 26.

Abstract

Metadata

Authors/Creators:
  • Garraghan, PM
  • Ouyang, X
  • Townend, P
  • Xu, J
Copyright, Publisher and Additional Information: © 2015, IEEE. Uploaded in accordance with the publisher's self-archiving policy. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.
Keywords: Cloud computing; Data analysis; Distributed Systems; Long Tail; datacenter; Stragglers; Monitoring
Dates:
  • Published: 20 July 2015
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds) > Institute for Computational and Systems Science (Leeds)
Funding Information:
FunderGrant number
EPSRCEP/F057644/1
Depositing User: Symplectic Publications
Date Deposited: 06 Aug 2015 13:23
Last Modified: 29 Jan 2018 10:53
Published Version: http://dx.doi.org/10.1109/ISORC.2015.39
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Identification Number: https://doi.org/10.1109/ISORC.2015.39

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