Wireless MAC mode selection using machine learning

    公开(公告)号:US10674440B2

    公开(公告)日:2020-06-02

    申请号:US16044648

    申请日:2018-07-25

    Abstract: In one embodiment, a network monitoring service trains, using a training dataset from one or more wireless networks, a machine learning model to output an optimized set of media access control (MAC) mode parameters for a wireless access point given an input set of network characteristics. The service receives a plurality of network characteristics associated with a particular wireless access point in a particular wireless network. The service determines, using the received network characteristics as input to the machine learning-based model, a set of MAC mode parameters for the particular wireless access point. The service controls the particular wireless access point to communicate with one or more clients in the particular wireless network based on the determined set of MAC mode parameters.

    Method and device for reducing multicast flow joint latency

    公开(公告)号:US10560359B2

    公开(公告)日:2020-02-11

    申请号:US15389960

    申请日:2016-12-23

    Abstract: In one embodiment, a method includes determining a first node as a current termination node of a first multicast flow; determining whether a link between the first node and a downstream next-hop node has available bandwidth to accommodate the first multicast flow, where the downstream next-hop node is not currently associated with the first multicast flow; and transmitting the first multicast flow to the downstream next-hop node according to a determination that the link between the first node and a downstream next-hop node has available bandwidth to accommodate the first multicast flow. According to some implementations, the method is performed by a controller with one or more processors and non-transitory memory, where the controller is communicatively coupled to a plurality of network nodes in a network.

    WIRELESS MAC MODE SELECTION USING MACHINE LEARNING

    公开(公告)号:US20200037233A1

    公开(公告)日:2020-01-30

    申请号:US16044648

    申请日:2018-07-25

    Abstract: In one embodiment, a network monitoring service trains, using a training dataset from one or more wireless networks, a machine learning model to output an optimized set of media access control (MAC) mode parameters for a wireless access point given an input set of network characteristics. The service receives a plurality of network characteristics associated with a particular wireless access point in a particular wireless network. The service determines, using the received network characteristics as input to the machine learning-based model, a set of MAC mode parameters for the particular wireless access point. The service controls the particular wireless access point to communicate with one or more clients in the particular wireless network based on the determined set of MAC mode parameters.

    Method and Device for Reducing Multicast Flow Join Latency

    公开(公告)号:US20180183697A1

    公开(公告)日:2018-06-28

    申请号:US15389960

    申请日:2016-12-23

    Abstract: In one embodiment, a method includes determining a first node as a current termination node of a first multicast flow; determining whether a link between the first node and a downstream next-hop node has available bandwidth to accommodate the first multicast flow, where the downstream next-hop node is not currently associated with the first multicast flow; and transmitting the first multicast flow to the downstream next-hop node according to a determination that the link between the first node and a downstream next-hop node has available bandwidth to accommodate the first multicast flow. According to some implementations, the method is performed by a controller with one or more processors and non-transitory memory, where the controller is communicatively coupled to a plurality of network nodes in a network.

    BANDWIDTH MANAGEMENT IN A NON-BLOCKING NETWORK FABRIC

    公开(公告)号:US20180062930A1

    公开(公告)日:2018-03-01

    申请号:US15346233

    申请日:2016-11-08

    Abstract: In one embodiment, a method includes discovering at a network controller, a topology and link capacities for a network, the network controller in communication with a plurality of spine nodes and leaf nodes, the link capacities comprising capacities for links between the spine nodes and the leaf nodes, identifying at the network controller, a flow received from a source at one of the leaf nodes, selecting at the network controller, one of the spine nodes to receive the flow from the leaf node based, at least in part, on the link capacities, and programming the network to transmit the flow from the spine node to one of the leaf nodes in communication with a receiver requesting the flow. An apparatus and logic are also disclosed herein.

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