Abstract: Provided is a method for performing an action based on a predictive outcome of an intended service deployment. The method includes receiving information pertaining to an intended service deployment. The method further includes receiving data pertaining to the intended service deployment based on the received information. The method further includes determining a predictive outcome of the intended service deployment based on the received data. The method further includes performing an action based on the predictive outcome.

Abstract: A service management system can obtain a service request message indicating an event that affects a user device of a telecommunications network. The system can store an indication of the event at a memory device that stores historical information of events and can process the event with a machine learning (ML) model that is trained based on the historical information to simulate the effect of the event on the telecommunications network. The system generates an output for display on a computing device. The output includes a recommendation and identifies an attribute of the event and a predicted value configured to reduce a workload or increase operational efficiency. The recommendation is configured to make the event actionable. The system receives feedback that a reviewer has acted on the recommendation. In response to the feedback, the system can re-train the ML model and configure the process for handling the service request.

Abstract: Provided is a control device that includes one or more processors configured to: select an agent gk that executes an action that represents allocation of a virtual network onto a physical network at a time point t from a plurality of agents; observe a state st at the time point t with an input of network configuration information of the physical network, network observation information, and user demand information; select and execute, on basis of an action value function Q representing an expected value of a sum total of a reward received in future, an action atk from possible actions for the agent gk; calculate a reward rt using of the action atk, the state st, and a state st+1 at a time point t+1; and update the action value function Q with use of the action ajk, the state sj, and the state sj+1, where 1?j?t is satisfied.

Abstract: Parties having different responsibilities and interests at a monitored location can be given a partial view of the totality of the sensor channels of data generated by the various sensors installed at the monitored location. The partial views deliver customized sets of data streams to customers. The selective distribution of sensor information accommodates the divergent interests and needs of parties responsible for tracking the various characteristics of a monitored location.

Abstract: Provided is an IoT GW (10), including a learning unit (131) configured to create, for each IoT device connected to the IoT GW (10), a normal communication model (122) that has learned a normal communication pattern of the IoT device; and a determination unit (132) configured to: determine, for learning by the learning unit (131), whether to interrupt, finish, continue, and resume learning based on a load of a learning environment; and control learning processing by the learning unit (131) based on a result of determination.

Abstract: A method, performed by a server, of adjusting allocation of computing resources to a plurality of virtualized network functions (VNFs), and the server are provided. The method includes: for processing at least one task related to user equipments (UEs) connected to the server, identifying a plurality of VNFs related to the task; obtaining predicted traffic expected to be generated in the server by processing the task via the plurality of VNFs; obtaining, from at least one associated server, status information of computing resources in the at least one associated server; and adjusting allocation of computing resources to the plurality of VNFs based on the status information of the computing resources in the at least one associated server and the predicted traffic, wherein the at least one associated server includes another server that processes the task.

Abstract: An edge computing telecommunications network is provided for efficiently generating and updating computing models for use at distributed devices connected to different edge compute sites of the network. A network orchestration system may track devices connected to the network and the edge compute sites to which they are connected. The devices may comprise limited computing power and may include sensors or other data collection mechanisms. Raw data may be provided from connected devices to one or more edge compute sites. Edge compute sites may be instructed, e.g., by the network orchestration system, whether to replicate the raw data, modify the data to make it ready for consumption by a computing model, replicate the modified data, refine the computing model, replicate the refined computing model, and/or share some or all of the raw data, modified data, and/or refined computing model with other edge computing sites and/or connected devices.

Abstract: An example method of determining a state of a key performance indicator (KPI) comprises: receiving one or more entity definitions, wherein each entity definition associates an entity with machine data pertaining to the entity; receiving a service definition for a service provided by one or more entities, the service definition including a reference to a corresponding entity definition of the entity definitions, wherein the service definition includes a respective reference for each of the one or more entities; receiving definitions of one or more KPIs, each KPI defined by a respective search query that produces a value derived from particular machine data, wherein the particular machine data is identified by the service definition, wherein each value is indicative of performance of the service at a point in time or during a period of time; deriving, by performing on the machine data a search query associated with the KPI, one or more KPI values for the KPI; selecting, among a plurality of states of the KPI, a

Abstract: A tag management system can include features to assist in developing a cross-vendor profile for individual visitors to content pages of a content site. The visitors to the content site can obtain universal identifiers usable by the content site to identify the visitors. The universal identifiers can be included in the content pages by the visitor end user systems so that browser tags that may not have native access to the universal identifier can access the universal identifiers. The universal identifiers may then be provided to tag vendor systems with associated visitor data, thereby enabling the tag vendor systems to provide processed or raw data that can be compared by individual universal identifiers. Using this processed data, the content site can prepare the cross-vendor profile of individual visitors and realize insights that may be unavailable using conventional systems and methods.

Abstract: The present disclosure provides techniques for recommending vendors using machine learning models. One example method includes generating a dependency graph based on one or more microservices in a transaction, wherein each node of the dependency graph corresponds to each microservice of the one or more microservices in the transaction, respectively, generating a first set of features using the dependency graph, predicting a first set of nodes that are likely to fail using a first machine learning model based on the first set of features, generating a second set of features using the dependency graph, predicting a second set of nodes that are likely to fail using a second machine learning model based on the second set of features, and applying one or more fixes to one or more microservices based on a combination of the first set of nodes and the second set of nodes.

Abstract: Implementations relate to interactions, over a wireless communication modality, between an automated assistant of an automobile computer system, and separate client device(s). In some of those implementations, the client device(s) can be paired with the automobile computer system, and the client device(s) and the automobile computer system can include separate instances of an automated assistant, which can be associated with different user accounts. In some additional or alternative implementations, particular actions to be performed by a local application of a client device can be advanced via user interaction with the automobile automated assistant, despite a counterpart to the local application not being installed directly on automobile computer system.

Abstract: A method, computer system, and computer program product are provided for detecting drift in predictive models for network devices and traffic. A plurality of streams of time-series telemetry data are obtained, the time-series telemetry data generated by network devices of a data network. The plurality of streams are analyzed to identify a subset of streams, wherein each stream of the subset of streams includes telemetry data that is substantially empirically distributed. The subset of streams of time-series data are analyzed to identify a change point. In response to identifying the change point, additional time-series data is obtained from one or more streams of the plurality of streams of time-series telemetry data. A predictive model is trained using the additional time-series data to update the predictive model and provide a trained predictive model.

Abstract: A method may include receiving a data flow of an application directed to the destination in a software-defined network (SDN). The method may also include identifying a classification of the application. The method may additionally include identifying a set of performance thresholds associated with the classification of the application. The method may also include determining a current performance of the data flow of the application in the SDN. The method may also include generating a performance score for the application based on the set of performance thresholds and the current performance of the data flow of the application in the SDN. The method may further include causing the performance score for the application to be presented via an interface.

Abstract: A network monitoring device may receive flow-tap information that identifies a traffic flow characteristic and a signed URL associated with a signed URL platform from a mediation device. The network device may map the traffic flow characteristic to the signed URL in an entry of a flow-tap filter that is maintained within a data structure of the network device. The network device may analyze, using the flow-tap filter, network traffic of the network to detect a traffic flow that is associated with the traffic flow characteristic. The network device may generate, based on detecting the traffic flow in the network traffic, a traffic flow copy that is associated with the traffic flow. The network device may provide, based on the signed URL, the traffic flow copy to the signed URL platform, wherein the traffic flow copy is to be accessible to an authorized user device via the signed URL.

Abstract: A system and method to monitor individual appliance performance. A monitor module is provided for aggregating data from a plurality of appliances wherein the module includes. Included in the monitor device is a gateway device configured to capture operational data relating to each of the plurality of appliances and an analyzing device configured to determine individual operational characteristics for each of the appliances from analysis of the captured operational data. A notification device is further provided which is configured to provide information to a user regarding the determined operational characteristics for each of the appliances.

Abstract: In general, techniques are described for network connectivity for non-colocated customers of a cloud exchange. A programmable network platform for the cloud exchange comprises processing circuitry configured to: configure a virtual network device in the data center to run a network service for a customer; receive, from the customer, a request for a remote port and network information for a network service provider connectivity service for the customer; assign, in response to receiving the request for the remote port, a remote port of the cloud exchange to the customer; and configure, in response to receiving the request for the remote port using the network information, the cloud exchange to connect the network service provider connectivity service to the virtual network device via the remote port of the cloud exchange.

Abstract: A remote network management platform may include persistent storage containing: (i) data related to a managed network, and (ii) a persona of a user. The remote network management platform may also include a platform application associated with a web-based user interface and using a portion of the data. The remote network management platform may also include a recommendation engine with access to a set of rules or a machine learning (ML) model corresponding to the platform application. The recommendation engine may be configured to: (i) read, from the persistent storage, the portion of the data and the persona; (ii) apply, to the portion of the data and the persona, the set of rules or the ML model to generate one or more recommendations; and (iii) transmit, by way of the web-based user interface and to the user, representations of the one or more recommendations.

Abstract: Techniques to generate network simulation scenarios are described. In one embodiment, an apparatus may comprise a records component operative to receive an example network configuration record; receive an example network operation record; a machine learning management component operative to generate a network operation model using a machine learning component based on the example network configuration record as an example input and the example network operation record as an example output; and a system-test component operative to receive a system-test network configuration record; and generate a system-test network operation record based on the system-test network configuration record using the network operation model. Other embodiments are described and claimed.

Abstract: Techniques are described with regard to application integration management. An associated computer-implemented method includes receiving from at least one user a request to map a plurality of data fields associated with a workflow during an application integration session and automatically mapping all data fields among the plurality of data fields for which a mapping confidence value is greater than or equal to a confidence level threshold set at a default value. The method further includes receiving mapping evaluations from each of the at least one user for each automatic data field mapping based upon the confidence level threshold set at the default value, processing at least one confidence level threshold adjustment input selection from one or more of the at least one user, and deriving at least one candidate default confidence level threshold value based upon the at least one confidence level threshold adjustment input selection.

Abstract: Provided is a method and apparatus for searching for a Maintenance End Point (MEP), and a storage medium. The method includes that: a chip of the MEP parses an obtained packet; the chip of the MEP determines whether a field of the parsed packet matches a field in a combination of a port and a Virtual Local Area Network (VLAN); and in a case where the field of the parsed packet matches the field in the combination of the port and the VLAN, the chip of the MEP determines that the MEP is found successfully.