Abstract:
Aspects of the subject disclosure may include, for example, a method including identifying, by a processing system including a processor, performance indicators for a flow on a communication network. The system determines a size criterion for the flow, and a flow shaping criterion based on the data type and including a threshold value of a performance indicator. If the size criterion is met, the system monitors the performance indicators and initiates a flow shaping procedure responsive to the flow shaping criterion being met. The system also detects a change in the performance indicators due to the flow shaping procedure, and discontinues the procedure during the flow, responsive to the changed performance indicators not meeting the flow shaping criterion. The system may also resume the flow shaping procedure during the flow if the performance indicators subsequently meet the flow shaping criterion. Other embodiments are disclosed.
Abstract:
Aspects of the subject disclosure may include, for example, setting a streaming rate cap for a client device; obtaining a bitrate ladder associated with the client device, wherein the bitrate ladder comprises a listing of a plurality of bitrates that the client device can request in connection with receiving streaming data; determining a boost rate for the client device, wherein the boost rate is greater than the streaming rate cap such that the boost rate enables the client device to receive the streaming data faster than the client device would otherwise receive the streaming data under the streaming rate cap, and wherein the boost rate is based upon the bitrate ladder; and enabling delivery to the client device of the streaming data up to the boost rate; wherein a network device is part of a network through which the streaming data is delivered to the client device. Other embodiments are disclosed.
Abstract:
A buffer classification system calculates first flow metrics for a first flow in response to receiving first packet level data. The system in response to receiving HTTP information, generates buffer emulation data and creates one or more data training sets using the first flow metrics and buffer emulation data, wherein training data used to create the one or more training data sets is further generated by computing an average throughput per second observed over different time windows during a video playback. The system in response to creating the one or more training data sets, generates one or more classifier rules used to determine a buffer condition of a flow. The system in response to receiving second packet level data, calculates second flow metrics for a second flow and predicts a buffer condition for the second flow based on the second flow metrics and the one or more classifier rules.
Abstract:
Concepts and technologies are disclosed herein for adaptive bit rate mobile video objective testing. A system can receive a plurality of screen-capture frames, where each of the plurality of screen-capture frames corresponds to a respective frame of an adaptive bit rate video stream being displayed on a screen of a test device. The system can create a screen-capture video stream and determine that the screen-capture video stream corresponds to a reference video stream that is non-annotated. The system can obtain a reference video signature package, align the screen-capture video stream with the reference video stream using the reference video signature package, generate full reference video quality performance indicators, and determine delivery quality performance indicators for the screen-capture video stream. The system can join the full reference video quality performance indicators and the delivery quality performance indicators to form an objective quality of experience data structure.
Abstract:
A method includes receiving, at a server associated with a network operator, a plurality of uniform resource locators (URLs) associated with a media stream provided to a client device. The method includes processing, at the server, the plurality of URLs to determine a quality of experience metric. Processing the plurality of URLs includes extracting first URL data from a first URL and second URL data from a second URL of the plurality of URLs. The first URL data includes a first segment identifier associated with a first segment of a media content item and a first bit rate identifier. The second URL data includes a second segment identifier associated with a second segment of the media content item and a second bit rate identifier. A quality of experience metric may be determined based at least in part on the first URL data and the second URL data.
Abstract:
A method includes receiving, at a device from a content source, a portion of a particular chunk of media content a particular quality level. The method includes receiving, at the device, network data about network conditions associated with the device in response to receipt of the portion. The method includes making, at the device, a determination based on the network data whether to download the particular chunk at a first quality level that is higher than the particular quality level based on the particular quality level and the data. The method includes, in response to the determination indicating to download the particular chunk at the first quality level: sending, to the content source from the device, a request for the particular chunk at the first quality level, and replacing the portion with the particular chunk at the first quality level.
Abstract:
Aspects of the subject disclosure may include, for example, a method in which a processing system obtains information from a network element of a communication network that includes cells each associated with user equipment devices (UEs); the information includes mapping data for each of the cells and the UEs associated with the respective cells, and the network element is in communication with the processing system via the communication network. The method also includes generating a historical record of cell load data representing content distributed to the cells from the processing system; determining that a cell is congested, based on the historical record; and performing a congestion shaping (CS) procedure for each of the UEs associated with the congested cell. Other embodiments are disclosed.
Abstract:
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.
Abstract:
Aspects of the subject disclosure may include, for example, determining a communication device initiating a first communication session with a video content server, and determining the communication device is downloading video content during the first communication session from the video content server over a portion of a communication network resulting in first downloaded video content. Further embodiments include determining a video content service associated with the first downloaded video content, and identifying the first downloaded video content as short-form video content in response to determining a group of network traffic features associated with the first downloaded video content during the first communication session. Additional embodiments include providing first instructions to a network device to adjust a group of network resources associated with the portion of the communication network. The network device adjusts the group of network resources associated with the portion of the communication network. Other embodiments are disclosed.
Abstract:
Aspects of the subject disclosure may include, for example, a method in which a processing system identifies a plurality of performance indicators comprising device performance indicators for a plurality of communication devices on a cellular network and network performance indicators for the cellular network. The method also includes obtaining historical data regarding the plurality of performance indicators for each of a series of time points during a past time period; the historical data for each of the plurality of performance indicators form an array of values for that performance indicator. The method further includes generating from each array a set of inputs to an algorithm for predicting a throughput of the cellular network during a future time period; the set of inputs comprises quantiles of the array, and the algorithm comprises a machine learning algorithm. Other embodiments are disclosed.