The disclosed system and method obtain a report of an issue reported by a user of the wireless telecommunication network, and historical information associated with the user and the wireless telecommunication network. The historical information includes multiple issues reported by users similar to the user, and multiple user statuses associated with the users similar to the user. The user status among the multiple user statuses includes active and inactive, indicating whether the user is an active member of the telecommunication network or has left the network. The system provides the historical information to an AI model, and obtains from the AI model a priority associated with the issue experienced by the user. The system causes a resolution of the issue based on the priority.

According to an aspect, there is provided a method for monitoring a communication network, the method comprising: monitoring (701) user plane information and control plane information for a first session provided by the communication network for a first wireless device; and correlating (703) the user plane information and the control plane information to determine if the first session was ended due to a soft drop, wherein a soft drop corresponds to a user of the wireless device intentionally terminating the first session due to service quality issues.

Aspects of the subject disclosure may include, for example, identifying a plurality of mobile devices implementing an application, and identifying a group of mobile devices from among the plurality of mobile devices according to a first movement pattern of the group of mobile devices. Further aspects can include identifying a first mobile edge compute (MEC) node at a first location according to a proximity threshold that does not include a MEC agent for the application, and identifying a second MEC node at a second location that includes the MEC agent for the application according to the proximity threshold. Additional aspects can include determining a first network relative performance (NRP) metric associated with a first communications between the group of mobile devices and the second MEC node. The first communications are associated with the application. Other embodiments are disclosed.

A poor-QoE assessment method and a related device are provided. The method includes: obtaining m data streams transmitted by a network device; screening the m data streams, and determining that p data streams in the m data streams and that meet a first preset condition are data streams corresponding to a first type; performing feature extraction on the data streams corresponding to the first type, to obtain known feature vectors corresponding to the first type; training, by using the known feature vectors corresponding to the first type, an untrained first poor-QoE assessment model, to obtain a trained first poor-QoE assessment model; and performing, by using the trained first poor-QoE assessment model, poor-QoE assessment on n data streams corresponding to the first type, to obtain a first poor-QoE assessment result. This method can be universally used instead of an application.

A method includes identifying a quality of service (QoS) policy associated with a tenant in view of a tenant identifier. The QoS policy includes a threshold value of a performance parameter. The method also includes receiving a service request from the tenant, estimating, in view of a subset of a plurality of historical records, an impact value indicating an impact of the service request on the performance parameter of the distributed storage system, determining, in view of the impact value, an estimated value of the performance parameter to result from servicing the service request of the tenant, and responsive to an evaluation of the estimated value of the performance parameter in view of the threshold value of the performance parameter, allocating computing resources of the multi-tenant distributed storage system to execute an operation associated with the service request.

A method includes identifying a quality of service (QoS) policy associated with a tenant in view of a tenant identifier. The QoS policy includes a threshold value of a performance parameter. The method also includes receiving a service request from the tenant, estimating, in view of a subset of a plurality of historical records, an impact value indicating an impact of the service request on the performance parameter of the distributed storage system, determining, in view of the impact value, an estimated value of the performance parameter to result from servicing the service request of the tenant, and responsive to an evaluation of the estimated value of the performance parameter in view of the threshold value of the performance parameter, allocating computing resources of the multi-tenant distributed storage system to execute an operation associated with the service request.

Techniques are described for onboarding virtualized network devices to a cloud-based WAN assurance system. For example, a virtualized network device receives, from a network device conductor that manages a plurality of network devices, a registration code for registering with the cloud-based WAN assurance system. In response to receiving the registration code and instructions, the network device sends the registration code to the cloud-based WAN assurance system. The cloud-based WAN assurance system verifies the network device based on the registration code, and assigns a distinct (e.g., unique) device identifier to the network device, and sends the distinct device identifier and a secret key to the network device. The network device uses the secret key to create a new secure connection with the cloud-based WAN assurance system, for streaming telemetry data to the WAN assurance system. The cloud-based WAN assurance system analyzes the network device telemetry data to provide WAN assurance.

Aspects of the present disclosure relate to wireless communications, and more particularly, to techniques that allow for enforcement of network latency fairness in multi-user gaming platforms. An example method generally includes identifying multiple user equipments (UEs) participating in a multi-user gaming platform across one or more wide area networks (WANs); and taking one or more actions to support latency fairness in delivery of information across the multiple users via the one or more WANs.

A system and method for measuring quality of experience (QoE) satisfaction for an application accessing a CSP network is described. A QoE requirement is associated with an application executed on a mobile device that is communicatively coupled to a CSP network. The QoE requirement for the application includes a QoE latency requirement, a QoE bandwidth requirement, and a QoE packet loss rate requirement. An edge-collection module gathers a radio access network (RAN) data set, and a core network (CN) data set that includes a network data analytics function (NWDAF) data set. The QoE network appliance generates a measured QoE score with the RAN data set, the CN data set, and the NWDAF data set. The measured QoE score is associated with the latency measurement, the bandwidth measurement, and the packet loss rate measurement. A subscriber ID is billed when a charging function determines the measured QoE satisfies the QoE requirement.

A system and method for resolving an unsatisfactory quality of experience (QoE) for an application executed on a wireless device that accesses a CSP network is described. A QoE network appliance generates an integrated event stream that includes a RAN data set, a CN data set, a NWDAF data set, a QoE latency measurement, a QoE bandwidth measurement, and a QoE packet loss rate measurement. A measured QoE score is generated with the RAN data set, the CN data set, and the NWDAF data set. The measured QoE score is associated with a QoE latency measurement, a QoE bandwidth measurement, and a QoE packet loss rate measurement. A robotics process automation (RPA) module receives the integrated event stream when the measured QoE score fails to satisfy the QoE requirement. The RPA module performs one or more automated actions to improve the measured QoE based on information from the integrated event stream.