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:
May. 23, 2023

Filed:

Apr. 22, 2020
Applicant:

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

Inventors:

Alok Tiagi, Sunnyvale, CA (US);

Farzad Ghannadian, Burlingame, CA (US);

Karen Hayrapetyan, Fremont, CA (US);

Laxmikant Vithal Gunda, San Jose, CA (US);

Sunitha Krishna, Saratoga, CA (US);

Ashot Aslanyan, Palo Alto, CA (US);

Anirban Sengupta, Saratoga, CA (US);

Assignee:

VMWARE, INC., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 47/78 (2022.01); H04L 47/125 (2022.01); G06K 9/62 (2022.01); H04L 9/40 (2022.01); H04L 41/22 (2022.01); H04L 67/01 (2022.01);
U.S. Cl.
CPC ...
H04L 47/781 (2013.01); G06K 9/6257 (2013.01); H04L 41/22 (2013.01); H04L 47/125 (2013.01); H04L 63/20 (2013.01); H04L 67/01 (2022.05);
Abstract

The disclosure provides an approach for workload labeling and identification of known or custom applications. Embodiments include determining a plurality of sets of features comprising a respective set of features for each respective workload of a first subset of a plurality of workloads. Embodiments include identifying a group of workloads based on similarities among the plurality of sets of features. Embodiments include receiving label data from a user comprising a label for the group of workloads. Embodiments include associating the label with each workload of the group of workloads to produce a training data set. Embodiments include using the training data set to train a model to output labels for input workloads. Embodiments include determining a label for a given workload of the plurality of workloads by inputting features of the given workload to the model.


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