Aspects of the subject disclosure may include, for example, obtaining, from a first source of information, a first bandwidth prediction, wherein the first bandwidth prediction is based upon historical bandwidth data that had been provided by a plurality of devices; obtaining, from a second source of information, a second bandwidth prediction, wherein the second bandwidth prediction is based upon network measurements, and wherein the network measurements are other than the historical bandwidth data that had been provided by the plurality of devices; selecting as a source of a future bandwidth prediction one of the first source of information and the second source of information, wherein the selecting is based upon a comparison of each of the first bandwidth prediction and the second bandwidth prediction to an actually obtained bandwidth of the device. Other embodiments are disclosed.

A method and system for constructing a content delivery network platform on heterogeneous resources are provided. The content delivery network platform includes a logic application layer and a basic resource layer. The construction method includes the following steps. After receiving an application creation request, the logic application layer determines actual resource configuration requirement information and resource type information of the application based on the application creation request, and sends the actual resource configuration requirement information and the resource type information to the basic resource layer. The basic resource layer creates a basic resource environment for the application based on the received actual resource configuration requirement information and the resource type information. Based on the self-defined logic application model, the present disclosure uses the ability modeling method to achieve the unified management of services constructed by a plurality of heterogeneous technical solutions such as physical machines, virtual machines, and containers.

An optimization platform system includes a network interface configured to communicate with a plurality user devices and a plurality of servers in a network; a processor communicatively coupled to the network interface; and memory storing instructions that, when executed, cause the processor to obtain network measurements including Quality of Service (QoS) measurements and one of measured Quality of Experience (QoE) measurements and inferred QoE measurements from the QoS measurements for one or more streams in the network, wherein each of the one or more streams has a type selected from a group consisting of a video stream, a Voice over Internet Protocol (VoIP) call, a gaming stream, and an Augmented Reality (AR)/Virtual Reality (VR) stream, and wherein the QoE measurements and the inferred QoE measurements of each of the one or more streams is based on the type of the respective stream, analyze the QoE measurements to determine poor QoE in the network, determine remedial actions in the network to repair the poor QoE, and cause implementation in the network.

A method and system for distributing content on a network through network-wide transactions is disclosed. The method and system monitors the network using triggered measurement of the performance of an element of the network, dynamically computing, based on the monitoring, the regions of the network with available performance capacity for the transaction to proceed at a given time, determining, based on the computing, a scheduled time for the transaction to proceed, and distributing the content according to a schedule related to the scheduled time.

A method for cross-domain service optimization is implemented on a computing device and includes defining at least one key quality indicator (KQI) target for at least one end-to-end (E2E) service, where the at least one E2E service crosses more than one domain of a communications network, receiving an indication of quality of experience (QoE) for the at least one E2E service, based on the indication of QoE, translating the at least one KQI target to at least one set of service optimization instructions for each domain from among the more than one domain, and for each domain, applying the service optimization instructions.

A data processing method, a server, and a data collection device are provided. The method includes: obtaining, by a server, first network key performance indicator KPI data and performance data of a first set-top box STB, where the first network KPI data is network KPI data of a first video service stream, and the first STB is an STB that receives the first video service stream; and calculating, by the server, first video quality of experience QoE of the first video service stream based on an associated model, the first network KPI data, and the performance data of the first STB, where the associated model is a model obtained through training based on historical data, and the associated model is used by the server to calculate video QoE based on network KPI data and performance data of an STB.

A device may receive a request to access a bundling service that manages access to an over-the-top service provided by an over-the-top service provider. The device may receive information that identifies a third party service provider and a user credential associated with the third party service provider. The third party service provider may be different from the over-the-top service provider, and the third party service provider may not provide the over-the-top service. The device may provide an authentication request, including the user credential, to a third party device associated with the third party service provider. The device may receive an authentication response from the third party device. The authentication response may indicate whether the third party device successfully authenticated the user credential. The device may selectively provide access to the bundling service based on receiving the authentication response.

Aspects of the subject disclosure may include, for example, a method including selecting a second network slice, according to first information and a first characteristic of a first service associated with a communication device. The first network slice is directed to route a first portion of user plane traffic between the communication device and the second network slice, while retaining a second portion according to a second characteristic of the first service. The first network slice retains control plane processing for the communication device. The second network slice is directed to facilitate providing the first service via the first portion of the user plane traffic. Anticipated resource usage information associated with the second network slice is determined and a first virtual network function is instantiated at the second network slice according to the anticipated resource usage information associated with the second network slice. Other embodiments are disclosed.

An apparatus having a device of a user and a computer is disclosed. The computer may be configured to (i) transfer a manifest to the device in response to a viewing session being opened. The manifest generally has a plurality of modified links to a plurality of bitrates of a video content. Each one of the modified links may include an identifier that is unique to the viewing session. The computer may also be configured to (ii) receive a particular one of the modified links from the device, (iii) log a presence of the viewing session, and (iv) generate a request by removing the identifier from the particular modified link.

A traffic analysis apparatus includes: a first means that estimates a state sequence from time-series data of communication traffic based on a hidden Markov model, and groups, into one group, a plurality of patterns with resembling state transitions in the state sequence to perform extraction of a state sequence, with taking the plurality of patterns grouped into one group as one state; and a second means that determines an application state corresponding to the time-series data based on the state sequence extracted by the first means and predetermined application characteristics.