Abstract: A network management system (NMS) is described that includes one or more processors coupled to memory storing network data. The one or more processors are configured to receive a query identifying a site and determine, based on the network data, a first set of troubleshooting issues for a wide area network (WAN) deployment at the site, a second set of troubleshooting issues for a wireless deployment at the site, and a third set of troubleshooting issues for a wired deployment at the site. The one or more processors are configured to determine, based on a user experience metric, a first troubleshooting issue from the first set of troubleshooting issues for the WAN deployment, a second troubleshooting issue from the second set of troubleshooting issues for the wireless deployment, and a third troubleshooting issue from the third set of troubleshooting issues for the wired deployment.

Abstract: A network management system (NMS) is described that provides a granular troubleshooting workflow at an application session level using an application session-specific topology from a client device to a cloud-based application server. During an application session of a cloud-based application, a client device running the application exchanges data through one or more access point (AP) devices, one or more switches at a wired network edge, and one or more network nodes, e.g., switches, routers, and/or gateway devices, to reach a cloud-based application server. For a particular application session, the NMS generates a topology based on network data received from a subset of network devices, e.g., client devices, AP devices, switches, routers, and/or gateways, that were involved in the particular application session over a duration of the particular application session. In this way, the NMS enables backward-looking troubleshooting of the particular application session.

Abstract: A network management system (NMS) is described that provides a granular troubleshooting workflow at an application session level using an application session-specific topology from a client device to a cloud-based application server. During an application session of a cloud-based application, a client device running the application exchanges data through one or more access point (AP) devices, one or more switches at a wired network edge, and one or more network nodes, e.g., switches, routers, and/or gateway devices, to reach a cloud-based application server. For a particular application session, the NMS generates a topology based on network data received from a subset of network devices, e.g., client devices, AP devices, switches, routers, and/or gateways, that were involved in the particular application session over a duration of the particular application session. In this way, the NMS enables backward-looking troubleshooting of the particular application session.

Abstract: This disclosure relates generally to wireless communications and, more particularly, to systems and methods for communication of slot offset information prior to communicating downlink control information. In one embodiment, a method performed by a communication node includes: determining slot offset indication information that classifies a slot offset information set as either a first kind or a second kind based on at least one of: high-layer configuration signaling and predefined information, and sending the slot offset indication information to a communication device.

Abstract: An example network analysis system includes a memory storing telemetry data received from a plurality of network devices, the plurality of network devices includes extract entity information and connectivity information from the received telemetry data, wherein the entity information represents one or more network devices of the plurality of network devices and the connectivity information represents network connections between one or more devices of the plurality of network devices; and store the connectivity information and entity information as a network topology graph in a graph database, wherein the entity information is stored as nodes of the network topology graph and the connectivity information is stored as edges of network topology graph, and wherein the network topology graph represents an organization level topology of the organization network.

Abstract: Techniques are described to enable a user equipment (UE) to save power consumption and/or can enable the UE to acquire the channel state in time without reducing the UE's data transmission efficiency. An example technique includes determining, by the communication device, an operating mode based on a first signaling, and operating the communication device in the operating mode, where the operating mode includes any one of a normal mode, a first power saving mode, a second power saving mode, a third power saving mode, or a fourth power saving mode.

Abstract: The disclosure discloses a fatty acid synthase inhibitor and application thereof and belongs to the technical field of medical biology. The fatty acid synthase inhibitor of the disclosure can significantly inhibit the activity of fatty acid synthase without affecting normal expression, and adjust the ratio of fatty acids in cells. The fatty acid synthase inhibitor of the disclosure has a good tumor proliferation inhibitory effect, can arrest the growth cycle of tumor cells in the interphase, prevent tumor cell division, inhibit tumor cell proliferation, promote tumor cell apoptosis and exert a tumor treatment effect, can be used to treat tumors and metabolism related diseases, and has an important clinical application prospect.

Abstract: An example network analysis system includes a memory storing telemetry data received from a plurality of network devices, the plurality of network devices includes extract entity information and connectivity information from the received telemetry data, wherein the entity information represents one or more network devices of the plurality of network devices and the connectivity information represents network connections between one or more devices of the plurality of network devices; and store the connectivity information and entity information as a network topology graph in a graph database, wherein the entity information is stored as nodes of the network topology graph and the connectivity information is stored as edges of network topology graph, and wherein the network topology graph represents an organization level topology of the organization network.

Abstract: An example method includes receiving, from a network device, data indicating characterizations of network traffic on a plurality of ports of the network device; determining, by processing circuitry, for each port of the plurality of ports, an indicator of a port type for the port based on the data indicating the characterizations of network traffic on the plurality of ports, wherein the port type indicates a link type of network traffic exchanged by the port; and outputting, by the processing circuitry, the indicator of the port type to an output device.

Abstract: An example system includes network devices at a site; and a network management system (NMS) that is configured to: identify a first network device of the plurality of network devices with which a network connection has been lost; identify, based on a network topology graph generated from the network data, one or more neighbor network devices of the plurality of network devices that are connected to the first network device; perform root cause analysis of the lost connection with the first network device based on the network data to identify a root cause of the lost connection; and send, to a neighbor network device selected from the one or more neighbor network devices and based on the identified root cause, instructions for the first network device to perform an action to remediate the lost connection, wherein the neighbor network device communicates the instructions to the first network device.

Abstract: A network management system (NMS) comprises one or more processors coupled to memory. The one or more processors of are configured to determine a list of network devices from the plurality of network devices based on an entity type and determine a suggested filter attribute based on the list of network devices and one or more of a user profile, a current state of the plurality of network devices, or a current state of the networking services. The one or more processors are further configured to output, in a user interface, an indication of the suggested filter attribute and, in response to receiving user input representative of a selection of the indication of the suggested filter attribute, determine a filtered list of network devices from the list of network devices using the suggested filter attribute and output, in the user interface, an indication of the filtered list of network devices.

Abstract: An example network analysis system includes a memory storing telemetry data received from a plurality of network devices, the plurality of network devices includes extract entity information and connectivity information from the received telemetry data, wherein the entity information represents one or more network devices of the plurality of network devices and the connectivity information represents network connections between one or more devices of the plurality of network devices; and store the connectivity information and entity information as a network topology graph in a graph database, wherein the entity information is stored as nodes of the network topology graph and the connectivity information is stored as edges of network topology graph, and wherein the network topology graph represents an organization level topology of the organization network.

Abstract: A network management system (NMS) is described that provides a granular troubleshooting workflow at an application session level using an application session-specific topology from a client device to a cloud-based application server. During an application session of a cloud-based application, a client device running the application exchanges data through one or more access point (AP) devices, one or more switches at a wired network edge, and one or more network nodes, e.g., switches, routers, and/or gateway devices, to reach a cloud-based application server. For a particular application session, the NMS generates a topology based on network data received from a subset of network devices, e.g., client devices, AP devices, switches, routers, and/or gateways, that were involved in the particular application session over a duration of the particular application session. In this way, the NMS enables backward-looking troubleshooting of the particular application session.

Abstract: Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

Abstract: Disclosed is a network management system that provides an interface to enable diagnostics and troubleshoot of a remotely managed multi-site network. Some embodiments provide a natural language interface, while other embodiments provide a chatbot type interface that communicates with a technician via traditional text information on a display screen. The diagnostic and troubleshooting capabilities search a central data store that receives device property information from each site of the multi-site network. Based on devices or users that match portions of the entity, queries to the data store are initiated to obtain additional data on the devices. A response to the query is then provided based on the properties of the devices.

Abstract: Techniques are described for monitoring network performance and managing network faults in a computer network. A cloud-based network management system stores path data received from a plurality of network devices operating as network gateways for an enterprise network, the path data collected by each network device of the plurality of network devices for one or more logical paths of a physical interface from the network device over a wide area network (WAN). The network management system determines, based on the path data, one or more WAN link health assessments, wherein the one or more WAN link health assessments include a success or failure state associated with one or more of service provider reachability, physical interface operation, or logical path performance; and in response to determining the at least one failure state, outputs a notification including identification of a root cause of the at least one failure state.

Abstract: Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

Abstract: Disclosed is a network management system that provides an interface to enable diagnostics and troubleshoot of a remotely managed multi-site network. Some embodiments provide a natural language interface, while other embodiments provide a chatbot type interface that communicates with a technician via traditional text information on a display screen. The diagnostic and troubleshooting capabilities search a central data store that receives device property information from each site of the multi-site network. Based on devices or users that match portions of the entity, queries to the data store are initiated to obtain additional data on the devices. A response to the query is then provided based on the properties of the devices.