Abstract:
Systems, methods, and computer-readable media for orchestrating data center resources and user access to data. In some examples, a system can determine, at a first time, that a user will need, at a second time, access to data stored at a first location, from a second location. The system can identify a node which is capable of storing the data and accessible by a device from the second location. The system can also determine a first service parameter associated with a network connection between the device and the first location and a second service parameter associated with a network connection between the device and the node. When the second service parameter has a higher quality than the first service parameter, the system can migrate the data from the first location to the node so the device has access to the data from the second location through the node.
Abstract:
In one embodiment, a method includes identifying at a network device, a characteristic of a video processed by a video service operating at an application layer, inserting the video characteristic into a header of a packet at the network device, and transmitting the packet on a service function path comprising a network function operable to use the video characteristic at a network layer. An apparatus and logic are also disclosed herein.
Abstract:
A cloud provider supports cloud-based services accessible to tenants of the cloud provider over a network. In the cloud provider, classification information including a cloud-identifier to identify the cloud provider, service-identifiers each to identify a respective one of the services, and tenant-identifiers each to identify a respective one of the tenants is maintained. The classification information is distributed within the cloud provider, including to the services, and may also be distributed outside of the cloud provider, to enable a respective tenant to exchange IP packets with, and thereby access, a respective service based on the classification information, wherein each IP packet includes the cloud-identifier, the service-identifier of the respective service, and the tenant-identifier of the respective tenant.
Abstract:
In one embodiment, a device in a network maintains a plurality of network paths for a media session. The device identifies a subset of data for the media session as requiring redundancy. The device sends a packet in the identified subset of data for the media session as redundant packets via two or more of the plurality of network paths for the media session. The device sends a particular packet outside of the identified subset of data for the media session non-redundantly via one of the plurality of network paths for the media session.
Abstract:
In one embodiment, a controller instructs an unmanned aerial vehicle (UAV) docked to a landing perch to perform a pre-flight test operation of a pre-flight test routine. The controller receives sensor data associated with the pre-flight test operation from one or more force sensors of the landing perch, in response to the UAV performing the pre-flight test operation. The controller determines whether the sensor data associated with the pre-flight test operation is within an acceptable range. The controller causes the UAV to launch from the landing perch based in part on a determination that UAV has passed the pre-flight test routine.
Abstract:
A network device may connect to a smart-enabled network. Once connected, the network device may receive a network address for a network management server (NMS). Having the network address for the NMS, the network device may generate a vCard comprising the attributes necessary for registering with the NMS. The network device may then communicate the vCard to the NMS. The NMS may then be configured to identify, register, and add the network device to a directory.
Abstract:
Methods are provided in which a collaboration server connects at least two participants via respective user devices to a collaboration session. The collaboration server further distributes, to the respective user devices, media stream data and one or more customized graphical items that are distinguishably displayed in the collaboration session. The one or more customized graphical items are displayed in a foreground or a background associated with a collaboration space of first participant of the at least two participants. The collaboration server further detects a selection, by one of the respective user devices, of a graphical item from the one or more customized graphical items displayed in the collaboration space and performs at least one action associated with the graphical item during the collaboration session based on detecting the selection of the graphical item.
Abstract:
Aggregated health information for a managed network may be retrieved and processed in response to changes to the managed network topology, configuration, or software. In response to receiving notification that a change to a component of the managed network has occurred, a change audit analysis engine can retrieve performance indicator information from components along a traceroute including the component which underwent the change. The retrieved performance indicator information can be processed by a memory based neural network to predict an impact of the change on the aggregated health of the managed network. The predicted impact can be compared to network health information retrieved through an ongoing basis and issues can be determined based on a comparison of the predict impact and the retrieved health information.
Abstract:
Systems, methods, and computer-readable mediums for distributing machine learning model training to network edge devices, while centrally monitoring training of the models and controlling deployment of the models. A machine learning model architecture can be generated at a machine learning structure controller. The machine learning model architecture can be deployed to network edge devices in a network environment to instantiate and train a machine learning model at the network edge devices. Performance reports indicating performance of the machine learning model at the network edge devices can be received by the machine learning structure controller from the network edge devices. The machine learning structure controller can determine whether to deploy another machine learning model architecture to the network edge devices based on the performance reports and subsequently deploy the another architecture to the network edge devices if it is determined to deploy the architecture based on the performance reports.
Abstract:
Techniques for associating manufacturer usage description (MUD) security profiles for Internet-of-Things (IoT) device(s) with secure access service edge (SASE) solutions, providing for automated and scalable integration of IoT devices with SASE frameworks. A MUD controller may utilize a MUD uniform resource identifier (URI) emitted by an IoT device to fetch an associated MUD file from a MUD file server associated with a manufacturer of the IoT device. The MUD controller may determine that a security recommendation included in the MUD file is to be implemented by a cloud-based security service provided by the SASE service and cause the IoT device to establish a connection with a secure internet gateway associated with the cloud-based security service. Additionally, or alternatively, the MUD file may include SASE extensions indicating manufacturer recommended cloud-based security services. Further, cloud-based security services may be implemented if local services are unavailable.