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    INTERACTIVE HIERARCHICAL NETWORK CHORD DIAGRAM FOR APPLICATION DEPENDENCY MAPPING
    84.
    发明申请
    INTERACTIVE HIERARCHICAL NETWORK CHORD DIAGRAM FOR APPLICATION DEPENDENCY MAPPING 审中-公开

    公开(公告)号：US20180270127A1

    公开(公告)日：2018-09-20

    申请号：US15972033

    申请日：2018-05-04

    Applicant: Cisco Technology, Inc.

    Inventor： Jackson Ngoc Ki Pang ,  Michael Standish Watts ,  Ali Parandehgheibi ,  Navindra Yadav

    IPC: H04L12/26 ,  H04L12/24

    Abstract: The technology visualizes data flows within a datacenter in an interactive hierarchical network chord diagram. Based on analyzed data describing data flows, a portion of the data flows that originate at the same first endpoint and terminate at the same second endpoint can be grouped. Subsequently, the dataflow monitoring system displays an interactive hierarchical network chord diagram to include a chord with a first endpoint and a second endpoint. The chord represents the grouped portion of data flows that originate at the same first endpoint and terminate at the same second endpoint. Upon receiving a selection of the chord or the first endpoint of the chord, the dataflow monitoring system expands the grouped portion of the data flows into a more granular representation of the network.

    Policy-driven compliance
    85.
    发明授权
    Policy-driven compliance 有权

    公开(公告)号：US10033766B2

    公开(公告)日：2018-07-24

    申请号：US15133155

    申请日：2016-04-19

    Applicant: Cisco Technology, Inc.

    Inventor： Sunil Kumar Gupta ,  Navindra Yadav ,  Michael Standish Watts ,  Ali Parandehgheibi ,  Shashidhar Gandham ,  Ashutosh Kulshreshtha ,  Khawar Deen

    IPC: H04L29/06 ,  H04L12/26

    Abstract: A network can achieve compliance by defining and enforcing a set of network policies to secure protected electronic information. The network can monitor network data, host/endpoint data, process data, and user data for traffic using a sensor network that provides multiple perspectives. The sensor network can include sensors for networking devices, physical servers, hypervisors or shared kernels, virtual partitions, and other network components. The network can analyze the network data, host/endpoint data, process data, and user data to determine policies for traffic. The network can determine expected network actions based on the policies, such as allowing traffic, denying traffic, configuring traffic for quality of service (QoS), or redirecting traffic along a specific route. The network can update policy data based on the expected network actions and actual network actions. The policy data can be utilized for compliance.

    CLUSTER DISCOVERY VIA MULTI-DOMAIN FUSION FOR APPLICATION DEPENDENCY MAPPING
    88.
    发明申请
    CLUSTER DISCOVERY VIA MULTI-DOMAIN FUSION FOR APPLICATION DEPENDENCY MAPPING 审中-公开
    通过多域融合的集群发现应用依赖映射

    公开(公告)号：US20160359680A1

    公开(公告)日：2016-12-08

    申请号：US15145493

    申请日：2016-05-03

    Applicant: Cisco Technology, Inc.

    Inventor： Ali Parandehgheibi ,  Omid Madani ,  Vimalkumar Jeyakumar ,  Ellen Christine Scheib ,  Navindra Yadav ,  Mohammadreza Alizadeh Attar

    IPC: H04L12/24 ,  H04L12/725 ,  H04L12/715

    Abstract: Application dependency mapping (ADM) can be automated in a network. The network can determine whether certain nodes form a cluster of a tier of an application. The network can monitor network data and process data for traffic passing through the network using a sensor network that provides multiple perspectives for the traffic. The network can analyze the network data and process data to determine respective feature vectors for nodes. A feature vector may represent a combination of the features corresponding to the network data and the features corresponding to the process data of a node. The network can compare the similarity of the respective feature vectors and determine each node's cluster based on similarity measures between nodes.

    Abstract translation: 应用程序依赖关系映射（ADM）可以在网络中自动化。 网络可以确定某些节点是否形成应用层的集群。 该网络可以监视网络数据并处理通过网络传输的流量的数据，该传感器网络为流量提供多个视角。 网络可以分析网络数据和处理数据，以确定节点的相应特征向量。 特征向量可以表示对应于网络数据的特征和与节点的过程数据相对应的特征的组合。 网络可以比较各个特征向量的相似度，并根据节点之间的相似性度量来确定每个节点的簇。

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