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:
Jul. 21, 2026

Filed:

Apr. 29, 2022
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Hagit Grushka, Beer-Sheva, IL;

Rachel Lemberg, Herzliya, IL;

Jeremy Samama, Herzliya, IL;

Eliya Habba, Petah Tikva, IL;

Yaniv Lavi, Tel Aviv-Jaffa, IL;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/50 (2006.01);
U.S. Cl.
CPC ...
G06F 9/5083 (2013.01); G06F 9/5038 (2013.01); G06F 9/5044 (2013.01); G06F 9/505 (2013.01); G06F 2209/508 (2013.01);
Abstract

The techniques disclosed herein enable systems to efficiently allocate computing resources for various computing workloads through a shared peak resource usage prediction. To achieve this, a predictive model analyzes a historical dataset defining resource usage of a computing environment for a past timeframe, and calculates a peak environment resource usage for a future or current timeframe. In addition, the predictive model estimates a peak number of computing workloads for the computing environment. Using the peak resource usage and/or the peak number of computing workloads, the system derives resource requests for allocating computing resources to a plurality of computing workloads. The computing workloads are subsequently assigned to computing nodes within the computing environment for execution. Furthermore, computing workloads within a computing node are configured to share computing resources to accommodate sudden surges in demand. In this way, the system can reduce computing resource wastage for computing environments.


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