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Output details

11 - Computer Science and Informatics

University of Leeds

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Output title

An Approach for Characterizing Workloads in Google Cloud to Derive Realistic Resource Utilization Models

Type
E - Conference contribution
Name of conference/published proceedings
7th IEEE International Symposium of Service-Oriented System Engineering (SOSE)
Volume number
-
Issue number
-
First page of article
49
ISSN of proceedings
-
Year of publication
2013
URL
-
Number of additional authors
3
Additional information

<02>Cloud inefficiency is largely attributed to poor understanding of workload and user characteristics, but rigorous analysis and modelling have been lacking. We present a pioneering (IEEE-SOSE'2013 best-paper award) academic effort in analysing very large real-world Cloud data. We combined our expertise in data science (TSB/Rolls-Royce STRAPP, £1.37M) to analyse Google Cloud's month-long operational tracelogs, with our modelling/simulation (ESRC MoSeS/GENeSIS, £2.4M) and middleware (CROWN/iVIC) expertise to develop realistic models for Cloud datacenters. Immediate impact on scientific research into Clouds includes our award-winning work [Xu4] and on-going collaboration with technology leaders: Google (John Wilkes) and Open Science Grid (Prof Miron Livny, HTCondor).

Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-