公开(公告)号：US20210409277A1

公开(公告)日：2021-12-30

申请号：US16915706

申请日：2020-06-29

Applicant: Cisco Technology, Inc.

Inventor： Sebastian Jeuk ,  Sridar Kandaswamy

IPC: H04L12/24

Abstract: A deployment system may generate and deploy network topology models within one or more workload resource domains. In some examples, the deployment system may implement a hierarchical data structure to store and manage multiple variations of a network topology models, in which network topology definitions and other characteristics may be inherited between related elements in the data structure. Data structures storing network topology models may be implemented as hierarchical levels of elements storing related, overlapping, and/or alternative portions of network topologies. A network topology model may be generated for deployment by combining the portions of network topologies stored within a branch of elements in the hierarchy, and the model may be deployed across one or more workload resource domains. Modifications to network topology models may be applied to individual elements and/or propagated to related elements based on the relationships and metadata defined for the in the hierarchical structure.

公开(公告)号：US20210392049A1

公开(公告)日：2021-12-16

申请号：US16901558

申请日：2020-06-15

Applicant: Cisco Technology, Inc.

Inventor： Sebastian Jeuk ,  Sridar Kandaswamy

IPC: H04L12/24 ,  H04L12/911 ,  G06N20/00

Abstract: Techniques are described herein for deploying, monitoring, and modifying network topologies comprising various computing and network nodes deployed across multiple workload resource domains. A deployment system may receive operational data from a network topology deployed across multiple workload resource domains, such as public or private cloud computing environments, on-premise data centers, and the like. The operational data may be provided to a trained machine-learning model, and output from the trained model may be used, along with constraint inputs and resource inventories of the workload resource domains, to determine updated topology models which may be deployed within the workload resource domains.

公开(公告)号：US10904099B2

公开(公告)日：2021-01-26

申请号：US16124866

申请日：2018-09-07

Applicant: Cisco Technology, Inc.

Inventor： Sridar Kandaswamy ,  Bob Melander

IPC: H04L12/24 ,  G06F30/3323

Abstract: In an embodiment, a computer-implemented method comprises receiving logical model input that specifies a logical topology model of networking elements and/or computing elements for deployment at least partially in a private cloud computing infrastructure and at least partially in a public cloud computing infrastructure; receiving resource input specifying an inventory of computing elements that are available at least partially in the private cloud computing infrastructure and at least partially in the public cloud computing infrastructure; automatically generating an intermediate topology comprising a set of deployment instructions that are capable of execution at least partially in the private cloud computing infrastructure and at least partially in the public cloud computing infrastructure to cause physical realization of a network deployment corresponding to the logical topology model; determining whether the intermediate topology is functionally equivalent to the logical topology model; in response to determining that the intermediate topology is functionally equivalent to the logical topology model, transmitting the deployment instructions at least partially to the private cloud computing infrastructure and at least partially to the public cloud computing infrastructure.

公开(公告)号：US20230188427A1

公开(公告)日：2023-06-15

申请号：US18105542

申请日：2023-02-03

Applicant: Cisco Technology, Inc.

Inventor： Sebastian Jeuk ,  Sridar Kandaswamy

IPC: H04L41/12 ,  H04L67/1001

CPC classification number: H04L41/12 ,  H04L67/1001

Abstract: Techniques are described herein for generating network topologies based on models, and deploying the network topologies across hybrid clouds and other computing environments that include multiple workload resource domains. A topology deployment system may receive data representing a logical topology model, and may generate a network topology for deployment based on the logical model. The network topology may include various services and/or other resources provided by different tenants in the computing environment, and tenant may be associated with different set of resources and deployment constraints. The topology deployment system may determine and generate the network topology to use the various resources and comply with various deployment constraints of the different tenants providing the services, and the tenants consuming the network topology.

公开(公告)号：US11671480B2

公开(公告)日：2023-06-06

申请号：US17390527

申请日：2021-07-30

Applicant: Cisco Technology, Inc.

Inventor： Sebastian Jeuk ,  Sridar Kandaswamy ,  Gonzalo Salgueiro

IPC: H04L67/10 ,  G06N20/00 ,  H04L41/0893 ,  H04L41/5041

CPC classification number: H04L67/10 ,  G06N20/00 ,  H04L41/0893 ,  H04L41/5041

Abstract: Techniques are described herein for generating and deploying network topologies to implement machine learning systems. A topology deployment system may receive data representing a logical model corresponding to a machine learning system, and may analyze the machine learning system to determine various components and attributes of the machine learning system to be deployed. Based on the components and attributes of the machine learning system, the topology deployment system may select target resources and determine constraints for the deployment of the machine learning system. A corresponding network topology may be generated and deployed across one or a combination of workload resource domains. The topology deployment system also may monitor and update the deployed network topology, based on performance metrics of the machine learning system and/or the current status of the system in a machine learning pipeline.

公开(公告)号：US20140140221A1

公开(公告)日：2014-05-22

申请号：US13680503

申请日：2012-11-19

Applicant: CISCO TECHNOLOGY, INC.

Inventor： Rajasekhar Manam ,  Venkata Naga Ramesh Ponnapalli ,  Sridar Kandaswamy

IPC: H04L12/24

CPC classification number: H04L41/12 ,  H04L41/0668 ,  H04L41/0886 ,  H04L41/0893 ,  H04L41/5054 ,  H04L49/70

Abstract: Embodiments generally provide techniques for mapping service modules on a network device. Embodiments identify a plurality of service modules, each configured to perform a respective service. A first one of the plurality of service modules is mapped to a first one of a plurality of virtual switches on the network device. Service policy information for a plurality of virtual switches is retrieved. The service policy information is indicative of service requirements for each of the plurality of virtual switches. Upon detecting an occurrence of a predefined event, embodiments determine a second one of the plurality of virtual switches to map the first service module to, based on the service policy information. The first service module is then mapped to the second virtual switch.

Abstract translation: 实施例通常提供用于在网络设备上映射服务模块的技术。 实施例识别多个服务模块，每个服务模块被配置为执行相应的服务。 多个服务模块中的第一个被映射到网络设备上的多个虚拟交换机中的第一个。 检索多个虚拟交换机的服务策略信息。 服务策略信息指示多个虚拟交换机中的每一个的服务需求。 在检测到预定事件的发生时，实施例基于服务策略信息确定多个虚拟交换机中的第二虚拟交换机，以将第一服务模块映射到该第一服务模块。 然后将第一个服务模块映射到第二个虚拟交换机。

公开(公告)号：US11575580B2

公开(公告)日：2023-02-07

申请号：US17335798

申请日：2021-06-01

Applicant: Cisco Technology, Inc.

Inventor： Sebastian Jeuk ,  Sridar Kandaswamy

IPC: H04L41/12 ,  H04L67/1001

Abstract: Techniques are described herein for generating network topologies based on models, and deploying the network topologies across hybrid clouds and other computing environments that include multiple workload resource domains. A topology deployment system may receive data representing a logical topology model, and may generate a network topology for deployment based on the logical model. The network topology may include various services and/or other resources provided by different tenants in the computing environment, and tenant may be associated with different set of resources and deployment constraints. The topology deployment system may determine and generate the network topology to use the various resources and comply with various deployment constraints of the different tenants providing the services, and the tenants consuming the network topology.

公开(公告)号：US20230032585A1

公开(公告)日：2023-02-02

申请号：US17390527

申请日：2021-07-30

Applicant: Cisco Technology, Inc.

Inventor： Sebastian Jeuk ,  Sridar Kandaswamy ,  Gonzalo Salgueiro

IPC: H04L29/08 ,  H04L12/24 ,  G06N20/00

Abstract: Techniques are described herein for generating and deploying network topologies to implement machine learning systems. A topology deployment system may receive data representing a logical model corresponding to a machine learning system, and may analyze the machine learning system to determine various components and attributes of the machine learning system to be deployed. Based on the components and attributes of the machine learning system, the topology deployment system may select target resources and determine constraints for the deployment of the machine learning system. A corresponding network topology may be generated and deployed across one or a combination of workload resource domains. The topology deployment system also may monitor and update the deployed network topology, based on performance metrics of the machine learning system and/or the current status of the system in a machine learning pipeline.

公开(公告)号：US11424989B2

公开(公告)日：2022-08-23

申请号：US16901558

申请日：2020-06-15

Applicant: Cisco Technology, Inc.

Inventor： Sebastian Jeuk ,  Sridar Kandaswamy

IPC: H04L41/12 ,  G06N20/00 ,  H04L47/70 ,  H04L41/16

Abstract: Techniques are described herein for deploying, monitoring, and modifying network topologies comprising various computing and network nodes deployed across multiple workload resource domains. A deployment system may receive operational data from a network topology deployed across multiple workload resource domains, such as public or private cloud computing environments, on-premise data centers, and the like. The operational data may be provided to a trained machine-learning model, and output from the trained model may be used, along with constraint inputs and resource inventories of the workload resource domains, to determine updated topology models which may be deployed within the workload resource domains.

公开(公告)号：US20210367852A1

公开(公告)日：2021-11-25

申请号：US17217532

申请日：2021-03-30

Applicant: Cisco Technology, Inc.

Inventor： Sridar Kandaswamy ,  Sebastian Jeuk

IPC: H04L12/24

Abstract: Techniques for deploying, monitoring, and modifying network topologies operating across multi-domain environments using formal models and weighting factors assigned to computing elements in the network topologies. The weighting factors restrict or allow the movement of various computing elements and/or element groupings to prevent undesirable disruptions or outages in the network topologies. Generally, the weighting factors may be determined based on an amount of disruption experienced in the network topologies if the corresponding computing element or grouping was migrated. As the amount of disruption caused by modifying a particular computing element increases, the weighting factor represents a greater measure of resistivity for migrating the computing element. In this way, topology deployment systems may allow, or disallow, the modification of particular computing elements based on weighting factors. Thus, the amount of disruption in the functioning of network topologies may be considered when optimizing the allocation of computing elements across multi-domain environments.