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[MKR18] Analyzing Traces from a Google Data Center
Conférence Internationale avec comité de lecture : IWCMC, July 2018, pp.1-4, Cyprus,
motcle:
Résumé:
Traces collected from an operational Google data
center over 29 days represent a very rich and useful source of
information for understanding the main features of a data center.
In this paper, we characterize the strong heterogeneity of jobs
and the medium heterogeneity of machine configurations. We
analyze the off-periods of machines. We study the distribution
of jobs per category, per scheduling class, per priority and per
number of tasks. The distribution of job execution durations
shows a high disparity, as does the job waiting time before being
scheduled. The resource requests in terms of CPU and memory
are also analyzed. The distribution of these parameter values
is very useful to develop accurate models and algorithms for
resource allocation in data centers.
Collaboration:
CEDRIC
BibTeX
| @inproceedings { | |||
| MKR18, | |||
| title | = | "{Analyzing Traces from a Google Data Center}", | |
| author | = | " P. Minet and I. Khoufi and E. Renault and S. Boumerdassi ", | |
| booktitle | = | "{IWCMC}", | |
| year | = | 2018, | |
| edition | = | "14", | |
| month | = | "July", | |
| pages | = | "1-4", | |
| address | = | " Cyprus", | |
| } | |||
