The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 15, 2020

Filed:

Apr. 12, 2018
Applicant:

Vmware, Inc., Palo Alto, CA (US);

Inventors:

Darren Brown, Seattle, WA (US);

Junyuan Lin, Seattle, WA (US);

Paul Pedersen, Palo Alto, CA (US);

Keshav Mathur, Palo Alto, CA (US);

Leah Nutman, Palo Alto, CA (US);

Peng Gao, Palo Alto, CA (US);

Xing Wang, Palo Alto, CA (US);

Assignee:

VMware, Inc., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/46 (2006.01); G06F 9/50 (2006.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06F 9/5027 (2013.01); G06N 7/00 (2013.01);
Abstract

Computational methods and systems that proactively manage usage of computational resources of a distributed computing system are described. A sequence of metric data representing usage of a resource is detrended to obtain a sequence of non-trendy metric data. Stochastic process models, a pulse wave model and a seasonal model of the sequence of non-trendy metric data are computed. When a forecast request is received, a sequence of forecasted metric data is computed over a forecast interval based on the estimated trend and one of the pulse wave or seasonal model that matches the periodicity of the sequence of non-trendy metric data. Alternatively, the sequence of forecasted metric data is computed based on the estimated trend and the stochastic process model with a smallest accumulated residual error. Usage of the resource by virtual objects of the distributed computing system may be adjusted based on the sequence of forecasted metric data.


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