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:
Jun. 25, 2024

Filed:

Aug. 02, 2021
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Chander Govindarajan, Bangalore, IN;

Sayandeep Sen, Bangalore, IN;

Palanivel Andiappan Kodeswaran, Bangalore, IN;

Sarang Sangram, Bangalore, IN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/50 (2006.01); G06F 9/445 (2018.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06F 9/5072 (2013.01); G06F 9/4451 (2013.01); G06F 9/5011 (2013.01); G06F 9/5077 (2013.01); G06N 20/00 (2019.01);
Abstract

Methods, systems, and computer program products for an automated resource request mechanism for heterogeneous infrastructure using profiling information are provided herein. A computer-implemented method includes obtaining resource utilization information, pertaining to multiple system resources, from multiple heterogeneous system infrastructure deployments; automatically learning resource interdependencies for the heterogeneous system infrastructure deployments by processing at least a portion of the resource utilization information using a first set of machine learning techniques; automatically determining performance profiles, with respect to the multiple system resources, for the multiple heterogeneous system infrastructure deployments by processing at least a portion of the resource utilization information and at least a portion of the learned resource interdependencies using a second set of machine learning techniques; predicting resource requests for at least one of the heterogeneous system infrastructure deployments using the determined performance profiles; and performing automated actions based on the resource request predictions.


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