A slice manager associated with a network access point of a telecommunication network can manage combinations of network slices and bandwidth parts for user equipment (UE). The bandwidth parts can have independently set numerologies, such as subcarrier spacing values. The UE can be configured to use one or more active bandwidth parts at a time, such that the slice manager can instruct the UE to use multiple active bandwidth parts simultaneously with respect to the same network slice or multiple network slices.

In one embodiment, a device obtains quality of experience metrics for an online application. The device generates a mapping between network paths traversed by traffic of the online application and the quality of experience metrics. The device identifies a core entity along the network paths that is responsible for degradation of the quality of experience metrics. The device sends an alert regarding the core entity, whereby the alert causes the traffic of the online application to avoid the core entity.

Systems and methods that adaptively model network traffic to predict network capacity utilization and quality of experience into the future. The adaptive model of network traffic may be used to recommend capacity upgrades based on a score expressed in a QoE space.

A node of a wireless communication network receives first data indicating a desired quality of experience level for user data traffic of a user of the wireless communication network. Based on a control policy and the desired quality of experience level, the node determines a rule for controlling the user data traffic. Further, the node obtains second data indicating an estimated quality of experience level for the user data traffic subject to control according to the rule. Based on the first data and the second data, the node adapts the control policy, e.g., using a reinforcement learning, RL, mechanism.

Embodiments include methods for a user equipment (UE), particularly for performing quality of experience (QoE) measurements configured by a wireless network. Such methods include receiving, from a radio access network node (RNN) in the wireless network, a request for QoE measurement reports that are available at the UE and that are associated with one or more services provided by the UE application layer. Such methods also include sending one or more QoE measurement reports to the RNN in accordance with the request. Other embodiments include complementary methods for a RNN, as well as UEs and RNNs configured to perform such methods.

Embodiments include methods for a user equipment (UE), particularly for performing quality of experience (QoE) measurements configured by a wireless network. Such methods include receiving, from a radio access network node (RNN) in the wireless network, a request for QoE measurement reports that are available at the UE and that are associated with one or more services provided by the UE application layer. Such methods also include sending one or more QoE measurement reports to the RNN in accordance with the request. Other embodiments include complementary methods for a RNN, as well as UEs and RNNs configured to perform such methods.

Techniques are described for monitoring application performance in a computer network. For example, a network management system (NMS) includes a memory storing path data received from a plurality of network devices, the path data reported by each network device of the plurality of network devices for one or more logical paths of a physical interface from the given network device over a wide area network (WAN). Additionally, the NMS may include processing circuitry in communication with the memory and configured to: determine, based on the path data, one or more application health assessments for one or more applications, wherein the one or more application health assessments are associated with one or more application time periods for a site, and in response to determining at least one failure state, output a notification including identification of a root cause of the at least one failure state.

A communication method and a system for converging a 5.sup.th-Generation (5G) communication system for supporting higher data rates beyond a 4.sup.th-Generation (4G) system with a technology for Internet of Things (IoT) is provided. The disclosure is applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as a smart home, a smart building, a smart city, a smart car, a connected car, health care, digital education, a smart retail, security and safety services. A method performed by a first entity performing a network data analytics function (NWDAF) is provided. The method includes receiving, from a second entity performing network function (NF), a first message for requesting observed service experience analytics, the first message including single-network slice selection assistance information (S-NSSAI) indicating a network slice, transmitting, to a third entity performing application function (AF) associated with the S-NSSAI, a second message for requesting service data associated with the observed service experience analytics, the second message including information on at least one application, receiving, from the third entity, the service data including at least one service experience for the at least one application, identifying the observed service experience analytics based on the service data, and transmitting, to the second entity, the observed service experience analytics.

Optimum software update transmission parameters are determined and used for transmitting a software update from a host to servers of a computer network. The software update is transmitted while the servers are live and required to meet certain quality of service requirements for tenants of the computer network. Transmission parameters for transmitting the software update are adjusted and updated based on service performance data. Based on iterative adjustments, optimum transmission parameters may be determined. Additionally or alternatively, machine learning is used to generate a model that determines predicted optimum transmission parameters. The predicted optimum transmission parameters may be initially used for transmitting a software update, while the transmission parameters continue to be adjusted throughout transmission.

A method for determining a Quality of Experience associated with a real-time communication session between user devices includes monitoring the real-time communication session and determining at least one quality indicator of the Quality of Experience, at least one first performance indicator of a Quality of Service, and at least one second performance indicator of the Quality of Service. Based on the quality indicator and the first performance indicator, the method determines, among a family of correlation functions indicative of the correlation between the Quality of Experience and a Quality of Service in respect of a generic real-time communication session, a correlation function which is indicative of the correlation between the Quality of Experience and the Quality of Service in respect of the monitored real-time communication session. Then the method applies the first performance indicator and the second performance indicator to the correlation function to determine said Quality of Experience.