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    CARBON-AWARE INTELLIGENT POWER MANAGER FOR CLUSTER NODES
    1.
    发明申请
    CARBON-AWARE INTELLIGENT POWER MANAGER FOR CLUSTER NODES 有权

    公开(公告)号：US20250085769A1

    公开(公告)日：2025-03-13

    申请号：US18759485

    申请日：2024-06-28

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Ganesh Byagoti Matad Sunkada ,  Thayumanavan Sridhar ,  Raj Yavatkar

    IPC: G06F1/3287

    Abstract: Example power management devices and techniques are described. An example computing device include one or more memories and one or more processors. The one or more processors are configured to determine, based on executing of at least one machine learning model, a measure of node criticality for a node of a cluster. The one or more processors are configured to determine, based on the measure of node criticality, a power savings measure of one or more power savings measures to be applied to the node. The one or more processors are configured to apply the power savings measure to the node.

    SELF LEARNING FIREWALL POLICY ENFORCER
    2.
    发明公开
    SELF LEARNING FIREWALL POLICY ENFORCER 审中-公开

    公开(公告)号：US20240179158A1

    公开(公告)日：2024-05-30

    申请号：US18472092

    申请日：2023-09-21

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Rahul Gupta ,  Ganesh Byagoti Matad Sunkada ,  Tarun Banka ,  Thayumanavan Sridhar ,  Raj Yavatkar

    IPC: H04L9/40 ,  G06N5/022 ,  G06N20/20

    CPC classification number: H04L63/1416 ,  G06N5/022 ,  G06N20/20

    Abstract: An example network system includes processing circuitry and one or more memories coupled to the processing circuitry. The one or more memories are configured to store instructions which, when executed by the processing circuitry, cause the network system to obtain first traffic session metrics data and execute a machine learning model to determine a traffic prediction based on the first traffic session metrics data. The instructions cause the network system to obtain second traffic session metrics data and determine an anomaly in traffic based on a comparison of the traffic prediction and the second traffic session metrics data. The instructions cause the network system to, based on the determination of the anomaly, generate an indication of the anomaly.

    SELF-LEARNING GREEN NETWORKS
    4.
    发明公开
    SELF-LEARNING GREEN NETWORKS 审中-公开

    公开(公告)号：US20230385697A1

    公开(公告)日：2023-11-30

    申请号：US18305181

    申请日：2023-04-21

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Thayumanavan Sridhar ,  Raj Yavatkar

    IPC: G06N20/00

    CPC classification number: G06N20/00

    Abstract: Techniques are described for determining the energy usage of a data center and invoking one or more actions to improve the energy usage of the data center. For example, a computing system may obtain energy usage data of a data center. The computing system may also determine, based on a comparison of the energy usage data of the data center to a percentage of energy provided by one or more renewable energy sources to the data center, a green quotient of the data center that specifies a value that indicates whether the data center is energy efficient. The computing system may further invoke, based on the green quotient of the data center that specifies a value that indicates the data center is not energy efficient, an action to improve energy usage of the data center.

    Self-learning service scheduler for smart NICs
    6.
    发明授权
    Self-learning service scheduler for smart NICs 有权

    公开(公告)号：US12289364B2

    公开(公告)日：2025-04-29

    申请号：US18640970

    申请日：2024-04-19

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Ganesh Byagoti Matad Sunkada ,  Thayumanavan Sridhar ,  Rajasree Krishnamoorthy ,  Raj Yavatkar ,  Jit Gupta ,  Krishna Kant

    IPC: H04L67/1008 ,  H04L41/16

    Abstract: An example method comprises determining, by an edge services controller, based on a respective predicted resource utilization value for each of a plurality of servers, a corresponding server weight for each of the plurality of servers; the plurality of servers comprising respective network interface cards (NICs), wherein each NIC of the plurality of NICs comprises an embedded switch and a processing unit coupled to the embedded switch; determining, by the edge services controller, based on a respective predicted resource utilization value for each of a plurality of services, a corresponding application weight for each of the plurality of services; and scheduling, by the edge services controller, based on the respective server weight for a server of the plurality of servers and the respective application weight for the service, a service of the plurality of services on the server.

    ENERGY AWARE WEIGHTED ECMP
    7.
    发明申请
    ENERGY AWARE WEIGHTED ECMP 有权

    公开(公告)号：US20250088452A1

    公开(公告)日：2025-03-13

    申请号：US18823384

    申请日：2024-09-03

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Vyasraj Satyanarayana ,  Ganesh Byagoti Matad Sunkada ,  Raj Yavatkar

    IPC: H04L45/12 ,  H04L43/10 ,  H04L45/50 ,  H04L47/125

    Abstract: Techniques are described for classifying packet flows to different paths of a computer network based at least in part on an energy cost of each of the different paths. In one example, a network device determines a weighted equal-cost multipath (wECMP) cost of each of different paths over which to forward packets. The different paths may include, for example, different interfaces of a network device, different links to which the network device is connected, or different links of an aggregated bundle of Ethernet links. The network device determines an energy cost of each of the paths. The network device modifies the wECMP cost of each path based at least in part on the energy cost of the path to obtain a modified wECMP cost. The network device load balances the packets over the paths in accordance with the modified wECMP cost.

    INTELLIGENT FIREWALL POLICY PROCESSOR
    8.
    发明公开
    INTELLIGENT FIREWALL POLICY PROCESSOR 审中-公开

    公开(公告)号：US20240179124A1

    公开(公告)日：2024-05-30

    申请号：US18472050

    申请日：2023-09-21

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Rahul Gupta ,  Ganesh Byagoti Matad Sunkada ,  Tarun Banka ,  Thayumanavan Sridhar ,  Raj Yavatkar

    IPC: H04L9/40 ,  H04L41/16

    CPC classification number: H04L63/0245 ,  H04L41/16

    Abstract: An example network system includes processing circuitry and one or more memories coupled to the processing circuitry. The one or more memories are configured to store instructions which cause the system to obtain telemetry data, the telemetry data being associated with a plurality of applications running on a plurality of hosts. The instructions cause the system to, based on the telemetry data, determine a subset of applications of the plurality of applications that run on a first host of the plurality of hosts. The instructions cause the system to determine a subset of firewall policies of a plurality of firewall polices, each of the subset of firewall policies applying to at least one respective application of the subset of applications. The instructions cause the system to generate an indication of the subset of firewall policies and send the indication to a management plane of a distributed firewall.

    SELF-LEARNING EGRESS TRAFFIC CONTROLLER
    9.
    发明公开
    SELF-LEARNING EGRESS TRAFFIC CONTROLLER 审中-公开

    公开(公告)号：US20240179074A1

    公开(公告)日：2024-05-30

    申请号：US18472059

    申请日：2023-09-21

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Rahul Gupta ,  Ganesh Byagoti Matad Sunkada ,  Tarun Banka ,  Thayumanavan Sridhar ,  Raj Yavatkar

    IPC: H04L41/16 ,  H04L41/14

    CPC classification number: H04L41/16 ,  H04L41/14

    Abstract: An example network system includes processing circuitry and one or more memories coupled to the processing circuitry. The one or more memories are configured to store instructions which, when executed by the processing circuitry, cause the network system to receive connection data related to an egress connection of an application service of an application. The instructions cause the network system to analyze the connection data to determine that the egress connection is an anomalous connection. The instructions cause the network system to generate a notification indicative of the egress connection being an anomalous connection and send the notification to a computing device.

    SELF-LEARNING GREEN APPLICATION WORKLOADS
    10.
    发明公开
    SELF-LEARNING GREEN APPLICATION WORKLOADS 审中-公开

    公开(公告)号：US20230342275A1

    公开(公告)日：2023-10-26

    申请号：US18305194

    申请日：2023-04-21

    Applicant: Juniper Networks, Inc.

    Inventor： Raja Kommula ,  Thayumanavan Sridhar ,  Raj Yavatkar

    IPC: G06F11/30 ,  G06F9/50

    CPC classification number: G06F11/3058 ,  G06F9/5088

    Abstract: Techniques are described for determining the energy usage of a data center and invoking one or more actions to improve the energy usage of the data center. For example, a computing system may obtain energy usage data of a data center deploying an application. The computing system may also determine, based on a comparison of the energy usage data of the data center deploying the application to a percentage of energy provided by one or more renewable energy sources to the data center, a green quotient of the application that specifies a value that indicates whether the data center deploying the application is energy efficient. The computing system may further invoke, based on the green quotient of the application that specifies a value that indicates the data center deploying the application is not energy efficient, an action to improve energy usage of the data center deploying the application.

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