公开(公告)号：US20240362078A1

公开(公告)日：2024-10-31

申请号：US18308848

申请日：2023-04-28

Applicant: Red Hat, Inc.

Inventor： Brian Gallagher ,  Michael Browne

IPC: G06F9/50

CPC classification number: G06F9/5072 ,  G06F9/5027 ,  G06F2209/503 ,  G06F2209/505

Abstract: A computing device determines that an executing first operator process is to be upgraded to a second operator process in an upgrade process, wherein the first operator process maintains on a cluster of compute nodes a desired identified state of an application. The computing device prior to initiating the second operator process, determines that the upgrade process will cause an initiation of a new container of the application to replace an existing container of the application. The computing device determines that an upgrade mode associated with the first operator process is a rolling upgrade mode, wherein the existing container and the new container will execute concurrently for a period of time. The computing device makes a determination whether computing resources needed to execute the existing container and the new container concurrently are available. The computing device takes an upgrade request action based on the determination.

公开(公告)号：US12078985B1

公开(公告)日：2024-09-03

申请号：US18470070

申请日：2023-09-19

Applicant: Morgan Stanley Services Group Inc.

Inventor： Sree Marudhalam ,  Vishal Deshmukh ,  Sujit Eapen

IPC: G06Q40/06 ,  G05B19/418 ,  G06F9/48 ,  G06F9/50 ,  G06F9/54

CPC classification number: G05B19/41895 ,  G05B19/41865 ,  G06F9/4881 ,  G06F9/5005 ,  G06F9/547 ,  G06F2209/503 ,  G06F2209/547 ,  G06Q40/06

Abstract: Managing tasks using an application-level blue-green topology with parallel cell infrastructure rails. Each cell infrastructure rail includes a dispatcher bot and a performer bot. The dispatcher bot is configured to prepare a work task based on a received request, and the performer bot performs the work task, resulting in performed work. A discovery server includes a service registry configured to store the states of the infrastructure rails. The discovery server receives the request for the work task, and sends the request to a dispatcher bot of a specific cell infrastructure rail based on the request and the states of the cell infrastructure rails. A respective workflow cell server receives the performed work. In the case that one cell infrastructure rail experiences a problem when processing the request, the cell infrastructure rails are switched to perform the request on the other cell infrastructure rail. The method implements the system.

公开(公告)号：US12073257B2

公开(公告)日：2024-08-27

申请号：US17216392

申请日：2021-03-29

Applicant: Red Hat, Inc.

Inventor： Guilherme H. Caponetto ,  Eder Ignatowicz ,  Alexandre Porcelli Bakos

IPC: G06F9/50 ,  H04L67/51

CPC classification number: G06F9/5072 ,  G06F9/5005 ,  G06F9/5077 ,  H04L67/51 ,  G06F2209/503

Abstract: Systems and methods for providing optional services for browser-based smart editing tools. In one implementation, a client extension on a client device receives a request to perform a function of a service. The client extension identifies an execution parameter for the service. The client extension determines a local service availability by evaluating a logical condition comprising the execution parameter. In view of the local service availability, the client extension causes the function of the service to be executed either on one of the client device or on a server device.

公开(公告)号：US20240249179A1

公开(公告)日：2024-07-25

申请号：US18099320

申请日：2023-01-20

Applicant: Accenture Global Solutions Limited

Inventor： Kaushik AMAR DAS ,  Kuntal DEY ,  Kapil SINGI ,  Vikrant KAULGUD ,  Sanjay PODDER ,  Gopal Sarma PINGALI ,  Teresa Sheausan TUNG

IPC: G06N20/00 ,  G06F9/50

CPC classification number: G06N20/00 ,  G06F9/505 ,  G06F2209/503 ,  G06F2209/509

Abstract: A method and system for training a federated learning model are disclosed. The method may include receiving the global federated learning model from the server via the client. The client may control remote computing resources. The method may further include identifying a spare computing instance from the remote computing resources and determine a threshold training load for training the global federated learning model based on a training load assigned to the client. The method may further include, in response to a processing capacity of the spare computing instance being sufficient to process the threshold training load, offloading the threshold training load to the spare computing instance and training the global federated learning model on the spare computing instance with the training dataset stored in a data source maintained by the client.

公开(公告)号：US20240220328A1

公开(公告)日：2024-07-04

申请号：US18093273

申请日：2023-01-04

Applicant: Oracle International Corpration

Inventor： Ming Fang ,  Xinyue Yu ,  Michal Piotr Prussak ,  Vladislavs Dovgalecs ,  Wei Gao

IPC: G06F9/50

CPC classification number: G06F9/505 ,  G06F2209/503

Abstract: Techniques are described for determining whether to process a job request. An example, method can include a device receiving a first message from a first stream, the first message comprising a job request from a tenant and a tenant identifier. The device can detect a base number of units permissible to be processed for the tenant over a unit of time. The device can detect a processing speed of a downstream processor of an asynchronous pipeline. The device can detect a number of messages in a second stream, the downstream processor configured to receive messages from the second stream. The device can determine a target throughput and a historical throughput for the tenant. The device can compare the target throughput with the historical throughput to determine whether to process the job request. The device can schedule the job request for processing based at least in part on the comparison.

公开(公告)号：US12020055B2

公开(公告)日：2024-06-25

申请号：US17356874

申请日：2021-06-24

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Xu Yang

IPC: G06F9/54 ,  G06F9/455 ,  G06F9/50

CPC classification number: G06F9/45558 ,  G06F9/5033 ,  G06F9/5077 ,  G06F2009/45562 ,  G06F2009/4557 ,  G06F2009/45595 ,  G06F2209/503 ,  G06F2209/505

Abstract: This application discloses a VNF service instantiation method and apparatus. The method is performed by a network functions virtualization orchestrator NFVO or a virtualized network function manager VNFM. The method includes: receiving a virtualized network function VNF instantiation request message; obtaining deployment information of a container service instance that needs to be invoked for VNF instantiation; determining one or more container as service clusters CaaS clusters based on the deployment information of the container service instance, and sending a container service instance creation request to a container as service manager CaaS manager in each of the one or more CaaS clusters; and receiving a container service instance creation success message from the CaaS manager. According to the foregoing solution, problems of cross-site deployment and management of a container service in an NFV scenario are resolved.

公开(公告)号：US20240193002A1

公开(公告)日：2024-06-13

申请号：US17799681

申请日：2022-06-10

Applicant: Baidu USA LLC ,  Baidu.com Times Technology (Beijing) Co., Ltd.

Inventor： HAOFENG KOU ,  DAVY HUANG ,  MANJIANG ZHANG ,  XING LI ,  LEI WANG ,  HUIMENG ZHENG ,  ZHEN CHEN ,  RUICHANG CHENG

IPC: G06F9/50 ,  G06F9/54

CPC classification number: G06F9/5066 ,  G06F9/5016 ,  G06F9/5044 ,  G06F9/544 ,  G06F2209/503

Abstract: A system obtains a performance profile corresponding to times taken to perform an inferencing by a machine learning (ML) model using a different number of processing resources from a plurality of processing resources. The system determines one or more groupings of processing resources from the plurality of processing resources, each grouping includes one or more partitions. The system calculates performance speeds corresponding to each grouping based on the performance profile. The system determines a grouping having a best performance speed from the calculated performance speeds. The system partitions the processing resources based on the determined grouping to perform the inferencing.

公开(公告)号：US12007747B2

公开(公告)日：2024-06-11

申请号：US17487609

申请日：2021-09-28

Applicant: FISHER-ROSEMOUNT SYSTEMS, INC.

Inventor： Anthony Amaro, Jr. ,  Mark J. Nixon ,  Gary K. Law ,  Claudio Fayad

IPC: G05B19/4155 ,  G06F9/50

CPC classification number: G05B19/4155 ,  G06F9/5077 ,  G05B2219/31229 ,  G06F2209/503

Abstract: A software defined (SD) process control system (SDCS) implements controller and other process control-related business logic as logical abstractions (e.g., application layer services executing in containers, VMs, etc.) decoupled from hardware and software computing platform resources. An SD networking layer of the SDCS utilizes process control-specific operating system support services to manage the usage of the computing platform resources and the creation, deletion, modifications, and networking of application layer services with devices disposed in the field environment and with other services, responsive to the requirements and needs of the business logic and dynamically changing conditions of SDCS hardware and/or software assets during run-time of the process plant (such as performance, faults, addition/deletion of hardware and/or software assets, etc.). Thus, dynamic (re-)allocation of hardware/software resources is primarily, if not entirely, and continually governed in real-time by present requirements and needs of application layer services as well as dynamically changing SDCS conditions.

公开(公告)号：US11977961B2

公开(公告)日：2024-05-07

申请号：US17069784

申请日：2020-10-13

Applicant: Ambeent Wireless

Inventor： Mustafa Ergen

IPC: G06F9/50 ,  G06N20/00

CPC classification number: G06N20/00 ,  G06F9/5072 ,  G06F9/5077 ,  G06F2209/5019 ,  G06F2209/502 ,  G06F2209/503 ,  G06F2209/505

Abstract: The invention generally relates to a method and system for distribution of computational capacity for a plurality of end-devices in different localities using a decentralized edge architecture. The method and system clusters a plurality of moving nodes capable of offering highly virtualized computational and storage resources utilizing an Artificial Intelligence (AI) model. The clustering is performed by utilizing two prediction models: a mobility prediction model and a theoretical framework. The mobility prediction model learns timing and direction of movements such as mobility patterns of each of the plurality of moving nodes, as to ascertain computational capacity for the given locale at a certain time. The theoretical framework performs sequential to parallel conversion in learning, optimization and caching algorithms of the AI model under contingent circumstances. Upon clustering, the cluster of moving nodes is utilized to process a plurality of workloads co-operatively for the set of end-devices in the given locale.

公开(公告)号：US11954524B2

公开(公告)日：2024-04-09

申请号：US17330583

申请日：2021-05-26

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Braulio Gabriel Dumba ,  Jun Duan ,  Nerla Jean-Louis ,  Muhammed Fatih Bulut ,  Sai Zeng

IPC: G06F9/46 ,  G06F9/48 ,  G06F9/50

CPC classification number: G06F9/4881 ,  G06F9/5005 ,  G06F2209/5011 ,  G06F2209/503

Abstract: A method for scheduling services in a computing environment includes receiving a service scheduling request corresponding to the computing environment and identifying a resource pool and a set of compliance requirements corresponding to the computing environment. The method continues by identifying target resources within the resource pool, wherein target resources are resources which meet the set of compliance requirements, and subsequently identifying a set of available target resources, wherein available target resources are target resources with scheduling availability. The method further includes analyzing the set of available target resources to determine a risk score for each available target resource and selecting one or more of the set of available target resources according to the determined risk scores. The method continues by scheduling a service corresponding to the service scheduling request on the selected one or more available target resources.