Learning from Cloud Latency Measurements

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00309828" target="_blank" >RIV/68407700:21230/15:00309828 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/7247457/" target="_blank" >http://ieeexplore.ieee.org/document/7247457/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCW.2015.7247457" target="_blank" >10.1109/ICCW.2015.7247457</a>

Result language
angličtina
Original language name
Learning from Cloud Latency Measurements
Original language description
Measuring, understanding, troubleshooting and optimizing various aspects of a Cloud Service hosted in remote datacenters is a vital, but non-trivial task. Carefully arranged and analyzed periodic measurements of Cloud-Service latency can provide strong insights into the service performance. A Cloud Service may exhibit latency and jitter which may be a compound result of various components of the remote computation and intermediate communication. We present methods for automated detection and interpretation of suspicious events within the multidimensional latency time series obtained by CLAudit, the previously presented planetary-scale Cloud-Service evaluation tool. We validate these methods of unsupervised learning and analyze the most frequent Cloud-Service performance degradations.
Czech name
—
Czech description
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2015 IEEE International Conference on Communication Workshop
ISBN
978-1-4673-6305-1
ISSN
—
e-ISSN
—
Number of pages
7
Pages from-to
1895-1901
Publisher name
IEEE Communications Society
Place of publication
Pomona, California
Event location
London
Event date
Jun 8, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000380459900311

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