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:
Dec. 03, 2024

Filed:

Jul. 13, 2022
Applicant:

Nec Laboratories America, Inc., Princeton, NJ (US);

Inventors:

Kunal Rao, Monroe, NJ (US);

Wang-Pin Hsiung, Santa Clara, CA (US);

Oliver Po, San Jose, CA (US);

Murugan Sankaradas, Dayton, NJ (US);

Srimat Chakradhar, Manalapan, NJ (US);

Anousheh Gholami, College Park, MD (US);

Assignee:

NEC Corporation, Tokyo, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/50 (2006.01); H04W 4/60 (2018.01); H04W 24/02 (2009.01);
U.S. Cl.
CPC ...
G06F 9/5038 (2013.01); H04W 4/60 (2018.02); H04W 24/02 (2013.01);
Abstract

A method for performing resource orchestration for microservices-based 5G applications in a dynamic, heterogenous, multi-tiered compute and network environment is presented. The method includes managing compute requirements and network requirements of a microservices-based application jointly by positioning computing nodes distributed across multiple layers, across edges and at a central cloud, identifying and modeling coupling relationships between compute and network resources for a plurality of microservices, when only application-level requirements are provided, to build coupling functions, solving a multi-objective optimization problem to identify how each of the plurality of microservices are deployed in the dynamic, heterogenous, multi-tiered compute and network environment by employing the coupling functions to jointly optimize resource usage of the compute and network resources across different compute and network slices, and deriving optimal joint network and compute resource allocation and function placement decisions.


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