Abstract: Presented herein are methodologies to on-board and monitor Internet of Things (IoT) devices on a network. The methodology includes receiving at a server, from a plurality of IoT devices communicating over a network, data representative of external environmental factors being experienced by individual ones of the plurality of IoT devices at a predetermined location; generating, using machine learning, an aggregated model of the external environmental factors at the predetermined location; receiving, at the server, a communication indicative that a new IoT device seeks to join the network at the predetermined location; receiving, from the new IoT device, data representative of external environmental factors being experienced by the new IoT device; determining whether there is a discrepancy between the external environmental factors of the new IoT device and the aggregated model; and when there is such a discrepancy, prohibiting the new IoT device from joining the network.

Abstract: Automatic, adaptive stimulus generation includes receiving, at a network device that is associated with a network or system, analytics data that provides an indication of how the network or system is responding to a set of test stimuli introduced into the network or system to facilitate an analysis operation. The network device analyzes the analytics data based on an intended objective for the analysis operation and generates control settings based on the analyzing. The control settings control creation of a subsequent stimulus to be introduced into the network or system during subsequent execution of the analysis operation.

Abstract: In one embodiment, a method includes receiving flight path data regarding the presence of an unmanned aerial vehicle (UAV) at a location at a future time, detecting the presence of the UAV at the location at the future time, determining radio identity data of the UAV using a radio mode of identification, determining optical identity data of the UAV using an optical mode of identification, and certifying the UAV based on a comparison of the radio identity data and the optical identity data to the flight path data.

Abstract: In one embodiment, a server determines a particular computer network outside of a lab environment to recreate, and also determines, for the particular computer network, hardware components and their interconnectivity, as well as installed software components and their configuration. The server then controls interconnection of lab hardware components within the lab environment according to the interconnectivity of the hardware components of the particular computer network. The server also installs and configures lab software components on the lab hardware components according to the configuration of the particular computer network. Accordingly, the server operates the installed lab software components on the interconnected lab hardware components within the lab environment to recreate operation of the particular computer network within the lab environment, and provides information about the recreated operation of the particular computer network.

Abstract: A network device receives a data packet including a source address and a destination address. The network device drops the data packet before it reaches the destination address and generates an error message indicating that the data packet has been dropped. The network device encapsulates the error message with a segment routing header comprising a list of segments. The first segment of the list of segments in the segment routing header identifies a remote server, and at least one additional segment is an instruction for handling the error message. The network device sends the encapsulated error message to the remote server based on the first segment of the segment routing header.

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, an apparatus includes a multi-socket motherboard, a processor connected to a first socket on the multi-socket motherboard, and an RDMA (Remote Direct Memory Access) interface module connected to a second socket on the multi-socket motherboard and in communication with the processor over a coherency interface. The RDMA interface module provides an inter-server interface between servers in an RDMA domain. A method for transferring data between servers with RDMA interface modules is also disclosed herein.

Abstract: A network device receives a data packet including a source address and a destination address. The network device drops the data packet before it reaches the destination address and generates an error message indicating that the data packet has been dropped. The network device encapsulates the error message with a segment routing header comprising a list of segments. The first segment of the list of segments in the segment routing header identifies a remote server. The network device sends the encapsulated error message to the remote server based on the first segment of the segment routing header.

Abstract: In one embodiment, a first wireless unmanned aerial vehicle (UAV)-locating signal is transmitted by a wireless network access point in a network based on a first UAV-locating mode selected from a plurality of UAV-locating modes. The wireless network access point receives a wireless signal in response to the first transmitted UAV-locating signal, the wireless signal indicative of a location of an airborne UAV, and causes the determination of the location of the airborne UAV based on the received wireless signal. The wireless network access point transmits a second wireless UAV-locating signal based on a second UAV-locating mode selected from the plurality of UAV-locating modes. The selected UAV-locating modes control an emission pattern of an antenna of the wireless network access point.

Abstract: In one embodiment, an autonomous carrier transports a fog computing module to an enclosure at a location determined to be in need of a particular fog computing resource, and aligns and anchors the fog computing module to the enclosure, where the aligning and anchoring is based on mating mechanical connectors on the fog computing module and enclosure. One or more electronic components of the fog computing module may then interface to the enclosure due to the anchoring, and the fog computing module activates at the location, accordingly. In one particular embodiment, the particular fog computing resource of the fog computing module is an additive resource to an existing fog computing resource module at the enclosure, and the existing fog computing resource module provides the mechanical connectors and interfaced electronic components of the enclosure.

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: Presented herein are segment-routing methods and systems that facilitate data plane signaling of a packet as a candidate for capture at various network nodes within a segment routing (SR) network. The signaling occurs in-band, via the data plane—that is, a capture or interrogation signal is embedded within the respective packet that carries a user traffic. The signaling is inserted, preferably when the packet is classified, e.g., at the ingress node of the network, to which subsequent network nodes with the SR network are signaled to capture or further inspect the packet for capture.

Abstract: Disclosed are systems, methods and non-transitory computer-readable mediums for dynamically presenting and updating a directed time graph displayed in a graphical user interface. In some examples, the method can include displaying a suggested path within a graphical user interface on a computer screen, the suggested path can include outstanding issues of elements of a network. The displaying the suggested path can include determining based on one or more factors an efficient ordering of the outstanding issues and ordering the outstanding issues based on the one or more factors. The method can also include monitoring, at regular intervals, updates to the one or more outstanding issues and automatically updating the suggested path, by a processor, based on the updates to the one or more outstanding issues.

Abstract: Various implementations disclosed herein enable transforming mutable wireless coverage areas using network coverage vehicles (NVCs) that are orchestrated by a network coverage controller. In various implementations, the method includes receiving coverage area performance characterization values from NCVs configured to provide a plurality of mutable wireless coverage areas. In various implementations, an arrangement of the mutable wireless coverage areas mutably defines the service area, which changes in accordance with changes to the arrangement of the mutable wireless coverage areas. In various implementations, the method also includes determining NCV operation adjustments for some of the NCVs based on the received coverage area performance characterization values in accordance with a service performance metric; and, altering an arrangement of one or more of the plurality of mutable wireless coverage areas within the service area by providing the NCV operation adjustments to some of the NCVs.

Abstract: Biometric masking includes testing video data and/or audio data from the video conference for biometric markers indicative of emotion or stress levels. If at least one of the biometric markers is detected with the testing, the video data and/or the audio data is edited to obfuscate the at least one of the biometric markers so that the video data and the audio data is transmitted to participants of the video conference with the at least one of the biometric markers obfuscated.

Abstract: In one embodiment, a first device in a network receives information regarding one or more nodes in the network. The first device determines a property of the one or more nodes based on the received information. The first device determines a degree of trustworthiness of the one or more nodes based on the received information. The first device attests to the determined property and degree of trustworthiness of the one or more nodes to a verification device. The verification device is configured to verify the attested property and degree of trustworthiness.

Abstract: In one embodiment, a classification device in a computer network analyzes data from a given device in the computer network, and classifies the given device as a particular type of device based on the data. The classification device may then determine whether a manufacturer usage description (MUD) policy exists for the particular type of device. In response to there being no existing MUD policy for the particular type of device, the classification device may then determine patterns of the analyzed data, classify the patterns into context-based policies, and generate a derived MUD policy for the particular type of device based on the context-based policies. The classification device may then apply one of either the existing or derived MUD policy for the given device within the computer network.

Abstract: Embodiments herein receive a request to reserve a fog computing resource for an end device, where the request includes a specified future time at which the fog computing resource will be used by the end device. It is determined that sufficient fog computing resources are available at the specified future time on a first fog node of a plurality of fog nodes. The fog computing resource of the first fog node is reserved for the specified future time, and an address corresponding to the first fog node is transmitted.

Abstract: Disclosed are systems, methods and non-transitory computer-readable mediums for dynamically presenting and updating a directed time graph displayed in a graphical user interface. In some examples, the method can include displaying a suggested path within a graphical user interface on a computer screen, the suggested path can include outstanding issues of elements of a network. The displaying the suggested path can include determining based on one or more factors an efficient ordering of the outstanding issues and ordering the outstanding issues based on the one or more factors. The method can also include monitoring, at regular intervals, updates to the one or more outstanding issues and automatically updating the suggested path, by a processor, based on the updates to the one or more outstanding issues.

Abstract: In one embodiment, a device in a network places a path of a service function chain into a testing state. The device causes a self-assessment instruction to be propagated along the path while the path is in the testing state. The device analyzes self-assessment results from nodes along the path. The device adjusts a state of the path based on the analyzed self-assessment results.