This application discloses a roaming charging method and apparatus. A blockchain network stores information related to roaming fee settlement, to reduce a possibility that the information related to roaming fee settlement is tampered with. In addition, a digital signature algorithm is used to sign roaming service statistics to generate an abstract, to further prevent the roaming service statistics from being tampered with. In this way, when a home carrier verifies a roaming account balance by using the roaming service statistics and a roaming charging rule, accuracy of a verification result can be ensured, and the home carrier can obtain an accurate roaming fee of a user.

A method for automatically generating service usage information in a telecommunication network, wherein the service usage information relates to a group of telecommunication transmission devices requesting a plurality of different types of telecommunication services on the telecommunication network, includes: for each request event of a telecommunication service of a telecommunication transmission device of the group of telecommunication transmission devices requested on the telecommunication network, generating an entry of the service usage information, wherein at least one type of the plurality of different types of telecommunication services is associated with each entry; and generating an aggregate entry, wherein the aggregate entry relates to the entries of the service usage information, and wherein the aggregate entry comprises aggregate information on each type of the plurality of different types of telecommunication services.

A flow tagging technique includes tagging a data flow at a plurality of points in the data flow. For example, the data flow can be tagged at a socket and at a proxy manager API. By tagging the data flow at multiple points, it becomes possible to map network service usage activities to the appropriate initiating applications.

An architecture to allow Multi-Access Edge Computing (MEC) billing and charge tracking, is disclosed. In an example, a tracking process, such as is performed by an edge computing apparatus, includes: receiving a computational processing request for a service operated with computing resources of the edge computing apparatus from a connected edge device within the first access network, wherein the computational processing request includes an identification of the connected edge device; identifying a processing device, within the first access network, for performing the computational processing request; and storing the identification of the connected edge device, a processing device identification, and data describing the computational processes completed by the processing device in association with the computational processing request.

Methods and apparatus for dynamic pricing and scheduling of network data transfers are disclosed. A system a plurality of network-accessible resources and a data transfer coordinator. In response to a client request for a network transfer of a data set, the coordinator determines, based at on a network-related metric of one or more resources, at least one time window during which a portion or all of the data set is transferable for a pricing rate below a threshold. The coordinator notifies the client of the time window and provides a duration-limited token authorizing data transfer during the window. The coordinator determines whether a network transmission of data on behalf of the client is valid based at least in part on a time at which the transmission is initiated and at least in part on a use of the token.

A system described herein may provide for the selection of a charging function (“CHF”) associated with a particular user equipment (“UE”). A particular CHF may be selected, from a group of candidate CHFs, based on CHF selection criteria respectively associated with the candidate CHFs and attribute information associated with the UE. The attribute information may describe attributes of the UE, profile information associated with the UE, and/or attributes of traffic and/or bearers associated with the UE.

An architecture to allow Multi-Access Edge Computing (MEC) billing and charge tracking, is disclosed. In an example, a tracking process, such as is performed by an edge computing apparatus, includes: receiving a computational processing request for a service operated with computing resources of the edge computing apparatus from a connected edge device within the first access network, wherein the computational processing request includes an identification of the connected edge device; identifying a processing device, within the first access network, for performing the computational processing request; and storing the identification of the connected edge device, a processing device identification, and data describing the computational processes completed by the processing device in association with the computational processing request.

A system for detecting fraud in international telecommunication traffic, includes: a transactions registry accessible by multiple operators and/or carriers; a logging module installed with multiple operators and/or carriers configured to add an entry in the transactions registry by an operator and/or carrier handling a call, wherein an entry comprises the calling number, the called number and timing information for the call; a fraud detection and classification module configured to: select from the transactions registry a group of correlated entries representing the call; compare the correlated entries to detect an anomaly due to fraud and to classify the call into a fraud type.

The present disclosure relates to a method for determining node metrics based on node field-value pairs and electronic activities. The method includes identifying a first node profile. The method includes identifying a plurality of electronic activities associated with the first node profile. The method includes identifying a first group of node profiles of a first category with a predetermined event. The method includes selecting a second group of node profiles. The method includes parsing the plurality of electronic activities to identify creation timestamps and participant characteristics of the electronic activities. The method includes generating an input array based on the timestamps and the participant characteristics. The method includes generating, for each of the second group of node profiles, a respective array. The method includes determining a probability score indicating a likelihood that the node profile belongs to the first category.

A VoWiFi registration control method and apparatus, an electronic device, and a server, are provided. A method on an electronic device side includes: obtaining first feature information of an electronic device; and controlling, in a case that the first feature information does not match second feature information, termination of VoWiFi registration in a process of performing VoWiFi registration. The first feature information is position feature information determined based on a first position of the electronic device, and the second feature information is position feature information determined based on a second position of the electronic device.