A method and apparatus for utilizing microslices in an enterprise wireless communication network to manage and control network performance. The microslice instances are monitored during network operation, for example at communication nodes, functional blocks, and end-to-end to provide Key Performance Indicators (KPIs). These KPI are compared with performance objectives, which may be Service Level Objectives (SLOs). If the performance objectives are not met by the KPIs, then one or more of the microslice instances may be dynamically adjusted until the performance objectives are sufficiently met. Alternatively, the lower priority microslice instances may be dropped (i.e., terminated) until the performance objectives are sufficiently met.

Disclosed herein are systems and methods for pattern-based QoS violation prediction. In one exemplary aspect, a method may comprise identifying a service on a computing device that is connected to a plurality of client devices and determining a plurality of micro-services comprised in the identified service. The method may comprise parsing access information to detect that a first client device is accessing a micro-service. The method may comprise determining, for a first period of time, QoS evaluation parameters for the access between the micro-service and the first client device. The method may comprise identifying changes in the QoS evaluation parameters within the first period of time, detecting a predetermined QoS violation pattern, and executing a QoS action based on the predetermined QoS violation pattern.

Disclosed herein are systems and methods for pattern-based QoS violation prediction. In one exemplary aspect, a method may comprise identifying a service on a computing device that is connected to a plurality of client devices and determining a plurality of micro-services comprised in the identified service. The method may comprise parsing access information to detect that a first client device is accessing a micro-service. The method may comprise determining, for a first period of time, QoS evaluation parameters for the access between the micro-service and the first client device. The method may comprise identifying changes in the QoS evaluation parameters within the first period of time, detecting a predetermined QoS violation pattern, and executing a QoS action based on the predetermined QoS violation pattern.

An automated system monitors network traffic to determine dependencies between different machines. These dependencies can be used to automatically develop a recovery plan for the machines, for example restoring servers in a certain order. This approach can also automatically adjust the recovery plan for changes in system configuration, for example as different servers come online or are taken offline or change their roles.

Various systems and methods for providing opportunistic placement of compute in an edge network are described herein. A node in an edge network may be configured to access a service level agreement related to a workload, the workload to be orchestrated for a user equipment by the node; modify a machine learning model based on the service level agreement; implement the machine learning model to identify resource requirements to execute the workload in a manner to satisfy the service level agreement; initiate resource assignments from a resource provider, the resource assignments to satisfy the resource requirements; construct a resource hierarchy from the resource assignments; initiate execution of the workload using resources from the resource hierarchy; and monitor and adapt execution of the workload based on the resource hierarchy in response to the execution of the workload.

Various systems and methods for providing opportunistic placement of compute in an edge network are described herein. A node in an edge network may be configured to access a service level agreement related to a workload, the workload to be orchestrated for a user equipment by the node; modify a machine learning model based on the service level agreement; implement the machine learning model to identify resource requirements to execute the workload in a manner to satisfy the service level agreement; initiate resource assignments from a resource provider, the resource assignments to satisfy the resource requirements; construct a resource hierarchy from the resource assignments; initiate execution of the workload using resources from the resource hierarchy; and monitor and adapt execution of the workload based on the resource hierarchy in response to the execution of the workload.

A latency processing system detects traffic at a cloud service end point and analyzes packets in the detected traffic to identify a network configuration of a client that is accessing the cloud service. Latency components corresponding to different parts of the network configuration are identified and quantified. A recommendation engine is controlled to generate and surface an output indicative of recommendations for reducing network latency.

A latency processing system detects traffic at a cloud service end point and analyzes packets in the detected traffic to identify a network configuration of a client that is accessing the cloud service. Latency components corresponding to different parts of the network configuration are identified and quantified. A recommendation engine is controlled to generate and surface an output indicative of recommendations for reducing network latency.

A method for notifying a quality of service (QoS) change includes determining that a change of a parameter of QoS notification control (QNC) of a non-guaranteed bit rate (non-GBR) bearing flow in a mobile network meets a reporting condition. The method further includes, in response to the determination that the change of the parameter of the QNC meets the reporting condition, transmitting a notification message to an application entity by an access network device through a core network entity.

The technologies described herein are generally directed to facilitating the allocation, scheduling, and management of network slice resources. According to an embodiment, a system can comprise a processor and a memory that can store executable instructions that, when executed by the processor, facilitate performance of operations. The operations can include receiving proposed contract data representative of a proposed contract for access by an application of a user equipment device to resources of a network slice usable for the access by the application. The operations can further include, based on the proposed contract data, storing governing contract data representative of a governing contract in a storage device, with the governing contract being selected to control the access by the application to the resources of the network slice. The operations can further include scheduling use of the resources of the network slice by the application based on the governing contract data.