Abstract: According to one or more embodiments of the disclosure, an asset inventory service executed by one or more devices receives telemetry data collected passively by a sensor application regarding a node in a network. The asset inventory service requests, after receiving the telemetry data, that the sensor application perform active discovery of nodes in the network. The asset inventory service receives active discovery data collected by the sensor application via active discovery of nodes in the network. The asset inventory service generates, based on the telemetry data and the active discovery data, an identity profile for the node.

Abstract: This application disclose a link configuration method, to configure a DSVPN tunnel interface parameter. A controller obtains a first link profile for a first site and a second link profile for a second site from a link profile library, where the link profile library includes a plurality of link profiles. The controller obtains preconfigured global configuration information, where the global configuration information includes an address pool. The controller generates a first link configuration parameter of the first site and a second link configuration parameter of the second site based on the address pool, the first link profile, and the second link profile and according to a preset link configuration rule. The controller sends the first link configuration parameter to the first site and sends the second link configuration parameter to the second site.

Abstract: An automated networking device replacement system includes a chassis housing in which management module and a fabric services subsystem are provided. The fabric services subsystem identifies that a first networking device has been provided in the chassis, and determines that the first networking device is a replacement for a second networking device. In response, the fabric services subsystem automatically identifies at least one fabric-services-based configuration that was performed on the second networking device, and automatically performs the at least one fabric-services-based configuration on the first networking device. The fabric services subsystem then transmits a management-module-based configuration instruction to the management module that causes the management module to automatically perform at least one management-module-based configuration on the first networking device that was performed on the second networking device.

Abstract: An example method includes obtaining, by one or more processors, data indicating resource dependencies between a plurality of resources in a network and event dependencies between a plurality of network events and one or more of the plurality of resources; generating a Bayesian model based on resource types of the plurality of resources and event types of the plurality of network events; receiving an indication of a fault in the network; collecting fault data and generating, based on the Bayesian model and the fault data, a plurality of root cause hypotheses for the fault; ordering the plurality of root cause hypotheses based on respective root cause probabilities associated with the plurality of root cause hypotheses; and outputting the ordered plurality of root cause hypotheses.

Abstract: Disclosed are example machine-learning approaches for determining maturity metrics of chatbot users. One or more datasets with words used during past conversations between a chatbot and a set of users with known maturity metrics are generated. A machine learning model is trained by applying machine learning to the one or more datasets such that the machine learning model is trained to output maturity metrics based on words received as inputs. A set of words or phrases spoken or written by the user during a conversation is fed to the machine learning model to determine a maturity metric of the user. A response is identified based on the determined maturity metric, and the response is presented during the conversation with the user. Words and phrases of a user conversing with a chatbot are used to determine the user's age or another maturity metric to generate responses that enhance the user experience.

Abstract: Aspects of the present disclosure include implementing fabric availability and synchronization (FAS) agents within a fabric network. In one example, a first FAS agent executing on a first network device may receive, from a second network device, a command to modify a configuration of a second network device. The first FAS may upgrade the configuration of the first network device based on the command from a current configuration to a new configuration. The first FAS agent increment a state identifier associated with the configuration of the first network device to a new state identifier associated with the new configuration. The first FAS agent may then transmit a control packet that includes the new state identifier. A second FAS agent executing on the second network device may receive the control packet and execute the command to update the configuration of the second network device to the new configuration.

Abstract: A tool for automatically generating incident management process efficiency metrics utilizing real-time communication analysis. The tool retrieves real-time conversation data from one or more communication sources, wherein the real-time conversation data includes one or more messages having data related to an information technology (IT) incident. The tool performs conversation analysis on the one or more messages. The tool determines one or more timestamps of interest for the IT incident from the one or more messages. The tool generates one or more incident management process efficiency metrics for the IT incident utilizing the one or more timestamps of interest. The tool predicts based, at least in part, on historical conversation data, an outcome for the IT incident. The tool sends the one or more incident management process efficiency metrics and the outcome for the IT incident to a user in a notification.

Abstract: Apparatuses and methods for identifying network anomalies. A method includes determining a cumulative anomaly score over a predefined time range based on a subset of historical PM samples and determining an anomaly ratio of a first time window and a second time window, based on the cumulative anomaly score. The method also includes determining one or more anomaly events coinciding with CM parameter changes based on the anomaly ratio; collating the PM, alarm, and CM data into a combined data set based on matching fields and timestamps; generating a set of rules linking one or more CM parameter changes and the collated data to anomaly events; and generating root cause explanations for CM parameter changes that are linked to anomaly events.

Abstract: The present invention relates to methods and apparatus for migrating and/or changing the allocation of network interface(s) or Internet Protocol address(es) of network interface(s) from one Pod, e.g., a failed Pod, to another Pod, e.g., a live Pod, in a Kubernetes system. An exemplary method of operating a Kubernetes system in accordance with an embodiment of the invention includes: establishing, by the Kubernetes system, a first service including a first Pod located on a first node and a second Pod located on a second node, allocating by the Kubernetes system an external network interface including an Internet Protocol address for use by the first Pod, the allocation of said external network interface for use by the first Pod being unknown to a first Kubelet managing the first node; and upon failure of the first Pod, changing allocation of the external network interface from the first Pod to the second Pod.

Abstract: An anomaly detection apparatus (10) includes a storage unit (14) that stores dictionary information (14b) in which a partial character string of a message representing a type of a message included in a text log output from a system and an ID set for the type of the message are associated with each other. The anomaly detection apparatus (10), when the message included in the text log output from the system is acquired, refers to the dictionary information (14b) stored in the storage unit (14), classifies the message included in the text log by the type, and assigns the ID to the message that has been classified; and detects an anomaly based on the ID assigned to the message.

Abstract: An NVMeoF gateway system includes a physical host device that communicates using a host NVMeoF protocol, and a physical target device that communicates using a target NVMeoF protocol. A networking device generates proxy host and target devices that are included in the same zone for the physical host and target devices, respectively. The networking device then converts first host NVMeoF protocol communications from the physical host device to first target NVMeoF protocol communications and provides them to the physical target device using the proxy host device, and converts second target NVMeoF protocol communications from the physical target device to second host NVMeoF protocol communications and provides them to the physical host device using the proxy target device. The first target NVMeoF protocol communications and the second host NVMeoF protocol communications configure the physical host device to exchange data with the physical target device.

Abstract: A method in which a communication device can be configured with a MAC address so that when the user logs into a network environment using a communication device from among a number of communication devices a MAC address is assigned to the user and is specific to the user. The MAC address assignment can be used for pairing with a communication device assigned to the user (e.g. a near-field communication device). A database containing MAC addresses can be connected to communication devices through a network and can provide user-specific MAC addresses that are readable into or otherwise transmittable to a predetermined communication device when a user logs into the network. The database can be managed by a server or other computer device of the network.

Abstract: Embodiments of a device and method are disclosed. In an embodiment, a method of automatic network service initiation involves pairing a first network device of a network service block (NSB) with an installer device at a customer site, at the first network device of the NSB, obtaining first network service configuration information from the installer device, performing automatic network service initiation of the first network device of the NSB based on the first network service configuration information, at a second network device of the NSB that is connected with the first network device of the NSB, obtaining address information of a cloud server from the first network device of the NSB, at the second network device of the NSB, obtaining second network service configuration information from the cloud server based on the address information, and performing automatic network service initiation of the second network device of the NSB based on the second network service configuration information.

Abstract: In one embodiment, a supervisory service for a software-defined wide area network (SD-WAN) uses a plurality of different decision thresholds for a machine learning-based classifier, to predict tunnel failures of a tunnel in the SD-WAN. The supervisory service captures performance data indicative of performance of the classifier when using the different decision thresholds. The supervisory service selects, based on the captured performance data, a particular decision threshold for the classifier, in an attempt to optimize the performance of the classifier. The supervisory service uses the selected decision threshold for the classifier, to predict a tunnel failure of the tunnel.

Abstract: An address management method, system, and device to avoid a problem that a same Internet Protocol (IP) address is assigned to different packet data unit (PDU) sessions and to effectively use IP addresses in an address pool. The method includes: obtaining, by a session management network element, an identifier of a user plane function network element serving a terminal and session information of the terminal; determining, by the session management network element based on the identifier of the user plane function network element and the session information, an address pool identifier corresponding to the session; sending, by the session management network element, the address pool identifier to a server, where the address pool identifier is used to assign an IP address to the session; and receiving, by the session management network element from the server, the IP address corresponding to the session.

Abstract: Disclosed are example machine-learning approaches for determining maturity metrics of chatbot users. One or more datasets with words used during past conversations between a chatbot and a set of users with known maturity metrics are generated. A machine learning model is trained by applying machine learning to the one or more datasets such that the machine learning model is trained to output maturity metrics based on words received as inputs. A set of words or phrases spoken or written by the user during a conversation is fed to the machine learning model to determine a maturity metric of the user. A response is identified based on the determined maturity metric, and the response is presented during the conversation with the user. Words and phrases of a user conversing with a chatbot are used to determine the user's age or another maturity metric to generate responses that enhance the user experience.

Abstract: Embodiments of a device and method are disclosed. In an embodiment, a method of automatic network service initiation involves obtaining, from a network service server at a first network device of a network service block (NSB), network address information using a network service client at a second network device of the NSB that is connected with the first network device, at the second network device of the NSB, obtaining network service configuration information based on the network address information, and, performing automatic network service initiation of the second network device of the NSB based on the network service configuration information.

Abstract: A computer-implemented method for seamlessly performing a maintenance operation on a stateful system includes mapping a network address of the stateful system to a primary server that uses a primary database to respond to incoming data requests. In response to receiving a maintenance request, the primary database is replicated to a secondary database of a secondary server. The secondary server is updated according to the maintenance request. The method further includes caching, in a replay buffer of the primary server, incoming data requests during the replicating. After the replicating, the data requests from the replay buffer are executed by the secondary server. Write operations to the primary server are disabled during the replicating, and the network address of the stateful system is mapped to the secondary server. Subsequently, the primary server is updated and reinstated by mapping the network address, and enabling the write operations.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor streaming media. An example apparatus includes a media calibrator to calibrate video data to a calibration time-base based on audio data, the video data and audio data associated with a media stream and a signature generator to generate a signature representative of the media stream based on the calibrated video data.

Abstract: A method for optimizing a slice orientation for an examination using a magnetic resonance machine is provided. One or more device limitation of the magnetic resonance machine is provided. The device limitation includes, for at least one of the one or more gradient axes, a maximum gradient strength and/or a maximum gradient slew rate. At least one measurement parameter value of the examination and an original slice orientation are also provided. Rotational-angle information is determined from device limitations, measurement parameter values, and the original slice orientation. The rotational-angle information is used to optimize the original slice orientation, and the magnetic resonance machine captures measurement data on the basis of the optimized slice orientation.