Aspects of the subject disclosure may include, for example, embodiments that comprise obtaining a data budget associated with a communication session for streaming video content over a communication network from a video content server, determining a first portion of the data budget that is associated with a first segment of the video content, and obtaining quality information associated with the video content from the video content server over the communication network. Further embodiments can include identifying a first group of tracks for the first segment, and determining a first target quality for the first segment based on the first portion of the data budget and the quality information. Other embodiments are disclosed.

An information handling system may include a processor; a memory; a network interface device to communicatively couple the information handling system to a first wireless communication networks of a plurality of wireless communication networks; an embedded subscriber identity module (eSIM) to provide data descriptive of wireless communication network-specific information to authenticate the information handling system; and an eSIM profile switching module to: monitor for signal strengths of each of a plurality of wireless communication networks. Upon discovering that the first wireless communication network has insufficient quality of service to sustain data transmission, send a request to a wireless communication network switching utility at a core communication network requesting roaming during a switch between the eSIM profile for a default wireless communication network to the second wireless communication network; and switch communication to the second wireless communication network while avoiding wireless service interruption with roaming if available.

A network device may receive a request for determination of a first non-session management policy control decision for a UE, and may provide an account limits request to another network device based on the request. The network device may receive, from the other network device, account limits for the UE, and may determine a first non-session management policy control service for the UE based on the account limits. The network device may cause the UE to be provisioned with a service based on the first non-session management policy control service, and may receive a request for determination of a second non-session management policy control decision for the UE. The network device may determine a second non-session management policy control service for the UE based on the account limits, and may cause the UE to be provisioned with a service based on the second non-session management policy control service.

One or more computing devices, systems, and/or methods for identifying anomalous behavior of users are provided. In an example, users of a telecommunication service provider may be segmented into a plurality of user segments based upon telecommunication service metrics associated with the users. A machine learning model may be trained using telecommunication service information associated with users of the first user segment to generate a trained machine learning model. Using the trained machine learning model, a forecast of telecommunication service usage associated with a first user segment of the plurality of user segments. A telecommunication service usage metric, associated with a user belonging to the first user segment, may be compared with a range indicated by the forecast. The user may be flagged as having anomalous behavior based upon a determination that one or more telecommunication usage metrics, associated with the user, are outside one or more ranges indicated by the forecast.

Methods, apparatus, and systems manage use of shared network resources among subscribers to a data communication service. In some implementations, a first metric is computed representing a subscriber's use of the shared network resources. A second metric may also be computed that represents the amount of network congestion of the shared network resources. Data derived from the first metric and the second metric may then be presented to the subscriber. The data may be transmitted to the subscriber over a network and/or the data may be displayed to the subscriber on an electronic display.

Disclosed is a 5G or pre-5G communication system to be provided to support a data transmission rate higher than that of a 4G communication system such as LTE. The present disclosure relates to a session management method through selection of a roaming operator and utilization of data usage rights of a local operator by a user in a 5G system. The user selects the local operator by switching the operator to a manual mode during roaming, accesses a data usage rights purchase agency through a limited service provided by the operator and then purchases the data usage rights of the local operator, and connects to a data network through authentication of a session by using authentication information included in the data usage rights.

An eNodeB or other cell access point device can receive demand data from mobile devices served by the cell. The demand data can represent an estimate of demand over a future period for network resources (e.g., bandwidth). The cell can aggregate this demand data and determine aggregation data for the time period or for various intervals of the time period, then transmit the aggregation data to the mobile devices. The aggregation data can operate as a collaborative approach to scheduling traffic. For example, data (e.g., delay tolerant data) can be shifted (e.g., delayed for a few seconds) based on an examination of the aggregation data in conjunction a determined priority of the data. Such can be applicable to data traffic not traditionally thought of as delay tolerant such as streaming video or web browsing, and can be accomplished without negatively impacting the quality of service or experience of the client.

The present disclosure provides a multi-user slice resource allocation method based on competitive game. In the method, first model a system as a two-tier architecture of virtual infrastructure service providers (VInPs) and users, and build a VInP utility model and a user utility model; then divide slice resource allocation into nodes and links, and build a node power consumption model and a link power consumption model, then determine a revenue of the VInP and a revenue of a user; and calculate a total revenue of a slice according to the revenue of the VInP and the revenue of the user, and use the total revenue of the slice as a network model; then solve the network model, where the VInP is used as a seller, the user is used as a buyer, the seller determines an initial price according to a total quantity of slice resources, and the buyer bids on the slice, and allocate the slice resources by using a competitive game mechanism. The method of the present disclosure may enhance the utility of the user, and improve a resource allocation effect.

A charging function device may include a processor configured to obtain subscription information associated with a user equipment (UE) device in a wireless communication network. The processor may be further configured to receive, from a gateway device, data flow information relating to data flows associated with the UE device; receive, from a policy device, policy information relating to policies applied to the data flows associated with the UE device; generate a record for the UE device based on the received data flow information and the received policy information, wherein the record identifies at least one account charge based on a particular data flow associated with the UE device; and provide the generated charging record to an account system.

A control plane function node may be used in a Fifth Generation (5G) Non-Standalone (NSA) architecture having Radio Access Network (RAN) level interworking between a Long-Term Evolution (LTE) RAN and a 5G New Radio (NR). The node obtains usage report data which are based on traffic of a user equipment (UE) via primary and secondary Radio Access Technologies (RATs). The node also obtains secondary RAT usage report data which are based on traffic of the UE via the secondary RAT. The node constructs a message which indicates a request for charging based on the usage report data and the secondary RAT usage report data. In constructing the message, the node populates, in association with a corresponding rating group and usage data of the UE, an identifier of a flow or bearer associated with secondary RAT usage, together with the secondary RAT usage report data.