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公开(公告)号：US11665106B2
公开(公告)日：2023-05-30
申请号：US17468517
申请日：2021-09-07
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Ali Tariq , Lianjie Cao , Faraz Ahmed , Puneet Sharma
IPC: H04L43/16 , H04L43/0882 , H04L47/80 , H04L47/78 , H04L47/70 , H04L47/762
CPC classification number: H04L47/803 , H04L43/0882 , H04L43/16 , H04L47/762 , H04L47/781 , H04L47/822
Abstract: Systems and methods are provided for updating resource allocation in a distributed network. For example, the method may comprise allocating a plurality of resource containers in a distributed network in accordance with a first distributed resource configuration. Upon determining that a processing workload value exceeds a stabilization threshold of the distributed network, determining a resource efficiency value of the plurality of resource containers in the distributed network. When a resource efficiency value is greater than or equal to the threshold resource efficiency value, the method may generate a second distributed resource configuration that includes a resource upscaling process, or when the resource efficiency value is less than the threshold resource efficiency value, the method may generate the second distributed resource configuration that includes a resource outscaling process. The resource allocation may transmit the second to update the resource allocation.
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公开(公告)号：US12133095B2
公开(公告)日：2024-10-29
申请号：US17503232
申请日：2021-10-15
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Faraz Ahmed , Lianjie Cao , Puneet Sharma
CPC classification number: H04W24/02 , G06N7/01 , G06N20/00 , H04W4/50 , H04W24/10 , H04W40/12 , H04W48/18
Abstract: Systems, methods, and computer-readable media are described for employing a machine learning-based approach such as adaptive Bayesian optimization to learn over time the most optimized assignments of incoming network requests to service function chains (SFCs) created within network slices of a 5G network. An optimized SFC assignment may be an assignment that minimizes an unknown objective function for a given set of incoming network service requests. For example, an optimized SFC assignment may be one that minimizes request response time or one that maximizes throughput for one or more network service requests corresponding to one or more network service types. The optimized SFC for a network request of a given network service type may change over time based on the dynamic nature of network performance. The machine-learning based approaches described herein train a model to dynamically determine optimized SFC assignments based on the dynamically changing network conditions.
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13.发明授权公开(公告)号：US11797340B2
公开(公告)日：2023-10-24
申请号：US16874479
申请日：2020-05-14
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Lianjie Cao , Faraz Ahmed , Puneet Sharma
IPC: G06F9/50 , G06F9/30 , G06N20/00 , G06F11/34 , G06F18/214 , G06F18/2415
CPC classification number: G06F9/5005 , G06F9/3009 , G06F9/505 , G06F9/5011 , G06F11/3409 , G06F18/214 , G06F18/24155 , G06N20/00
Abstract: Systems and methods are provided for optimally allocating resources used to perform multiple tasks/jobs, e.g., machine learning training jobs. The possible resource configurations or candidates that can be used to perform such jobs are generated. A first batch of training jobs can be randomly selected and run using one of the possible resource configuration candidates. Subsequent batches of training jobs may be performed using other resource configuration candidates that have been selected using an optimization process, e.g., Bayesian optimization. Upon reaching a stopping criterion, the resource configuration resulting in a desired optimization metric, e.g., fastest job completion time can be selected and used to execute the remaining training jobs.
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公开(公告)号：US20230275848A1
公开(公告)日：2023-08-31
申请号：US18311430
申请日：2023-05-03
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Ali Tariq , Lianjie Cao , Faraz Ahmed , Puneet Sharma
IPC: H04L47/80 , H04L47/78 , H04L43/16 , H04L47/70 , H04L43/0882 , H04L47/762
CPC classification number: H04L47/803 , H04L47/781 , H04L43/16 , H04L47/822 , H04L43/0882 , H04L47/762
Abstract: Systems and methods are provided for updating resource allocation in a distributed network. For example, the method may comprise allocating a plurality of resource containers in a distributed network in accordance with a first distributed resource configuration. Upon determining that a processing workload value exceeds a stabilization threshold of the distributed network, determining a resource efficiency value of the plurality of resource containers in the distributed network. When a resource efficiency value is greater than or equal to the threshold resource efficiency value, the method may generate a second distributed resource configuration that includes a resource upscaling process, or when the resource efficiency value is less than the threshold resource efficiency value, the method may generate the second distributed resource configuration that includes a resource outscaling process. The resource allocation may transmit the second to update the resource allocation.
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15.发明申请公开(公告)号：US20220342649A1
公开(公告)日：2022-10-27
申请号：US17236884
申请日：2021-04-21
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Lianjie Cao , Anu Mercian , Diman Zad Tootaghaj , Faraz Ahmed , Puneet Sharma
Abstract: Embodiments described herein are generally directed to an edge-CaaS (eCaaS) framework for providing life-cycle management of containerized applications on the edge. According to an example, declarative intents are received indicative of a use case for which a cluster of a container orchestration platform is to be deployed within an edge site that is to be created based on infrastructure associated with a private network. A deployment template is created by performing intent translation on the declarative intents and based on a set of constraints. The deployment template identifies the container orchestration platform selected by the intent translation. The deployment template is then executed to deploy and configure the edge site, including provisioning and configuring the infrastructure, installing the container orchestration platform on the infrastructure, configuring the cluster within the container orchestration platform, and deploying a containerized application or portion thereof on the cluster.
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Patent Agency Ranking
公开(公告)号：US10827020B1
公开(公告)日：2020-11-03
申请号：US16592560
申请日：2019-10-03
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Lianjie Cao , Puneet Sharma
Abstract: Example implementations relate to assigning microservices to cluster nodes. A sidecar proxy may be deployed at a data plane of a distributed service. The sidecar proxy may monitor telemetry data between microservices of the distributed service. A communication pattern may be determined from the telemetry data of the distributed service. Each microservice of the distributed service may be assigned to a cluster node based on the communication pattern.
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公开(公告)号：US20250141736A1
公开(公告)日：2025-05-01
申请号：US18498777
申请日：2023-10-31
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Chinlin Chen , Uyen T. Chau , Faraz Ahmed , Lianjie Cao
IPC: H04L41/0803 , H04L41/08
Abstract: A network management system (NMS) that can provision and manage a network is provided. During operation, the NMS can determine, for a respective network device in the network, connectivity information indicating how the network device is connected within the network and a device profile of the network device. The NMS can then determine a connectivity tier of the network device in the network based on the connectivity information. The connectivity tier can correspond to a placement of the network device in a hierarchy of network devices in the network. The NMS can select a device persona associated with the connectivity tier. Here, the device persona indicates specification and configurations for the network device. The NMS can send, to the network device, configuration information that configurates the device persona on the network device.
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公开(公告)号：US12132668B2
公开(公告)日：2024-10-29
申请号：US18311430
申请日：2023-05-03
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Ali Tariq , Lianjie Cao , Faraz Ahmed , Puneet Sharma
IPC: H04L47/78 , H04L43/0882 , H04L43/16 , H04L47/70 , H04L47/762 , H04L47/80
CPC classification number: H04L47/803 , H04L43/0882 , H04L43/16 , H04L47/762 , H04L47/781 , H04L47/822
Abstract: Systems and methods are provided for updating resource allocation in a distributed network. For example, the method may comprise allocating a plurality of resource containers in a distributed network in accordance with a first distributed resource configuration. Upon determining that a processing workload value exceeds a stabilization threshold of the distributed network, determining a resource efficiency value of the plurality of resource containers in the distributed network. When a resource efficiency value is greater than or equal to the threshold resource efficiency value, the method may generate a second distributed resource configuration that includes a resource upscaling process, or when the resource efficiency value is less than the threshold resource efficiency value, the method may generate the second distributed resource configuration that includes a resource outscaling process. The resource allocation may transmit the second to update the resource allocation.
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19.发明公开公开(公告)号：US20230325166A1
公开(公告)日：2023-10-12
申请号：US18328287
申请日：2023-06-02
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Lianjie Cao , Anu Mercian , Diman Zad Tootaghaj , Faraz Ahmed , Puneet Sharma
Abstract: Embodiments described herein are generally directed to an edge-CaaS (eCaaS) framework for providing life-cycle management of containerized applications on the edge. According to an example, declarative intents are received indicative of a use case for which a cluster of a container orchestration platform is to be deployed within an edge site that is to be created based on infrastructure associated with a private network. A deployment template is created by performing intent translation on the declarative intents and based on a set of constraints. The deployment template identifies the container orchestration platform selected by the intent translation. The deployment template is then executed to deploy and configure the edge site, including provisioning and configuring the infrastructure, installing the container orchestration platform on the infrastructure, configuring the cluster within the container orchestration platform, and deploying a containerized application or portion thereof on the cluster.
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公开(公告)号：US20230123074A1
公开(公告)日：2023-04-20
申请号：US17503232
申请日：2021-10-15
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Faraz Ahmed , Lianjie Cao , Puneet Sharma
Abstract: Systems, methods, and computer-readable media are described for employing a machine learning-based approach such as adaptive Bayesian optimization to learn over time the most optimized assignments of incoming network requests to service function chains (SFCs) created within network slices of a 5G network. An optimized SFC assignment may be an assignment that minimizes an unknown objective function for a given set of incoming network service requests. For example, an optimized SFC assignment may be one that minimizes request response time or one that maximizes throughput for one or more network service requests corresponding to one or more network service types. The optimized SFC for a network request of a given network service type may change over time based on the dynamic nature of network performance. The machine-learning based approaches described herein train a model to dynamically determine optimized SFC assignments based on the dynamically changing network conditions.
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