AT&T Intellectual Property I, LP

University of Michigan

University of Connecticut

Chemocentryx, Inc.

At&t Mobility II LLC

At+t Corp.

Purdue Research Foundation

Indiana University

Other

Lucent Technologies Inc.

Alcatel Lucent

University of Minnesota

University of Southern California

Princeton University

At&t Mobolity II LLC

Subhabrata Bapi Sen

Oliver Spatscheck

Alexandre Gerber

Feng Qian

Zhuoqing Morley Mao

Zhaoguang Wang

Nicholas G Duffield

Carsten Lund

Lee Breslau

Yin Sheng Zhang

Yanyuan Qin

Bing Wang

Emir Halepovic

Shuai Hao

James Bradley Aggen

Andrew M K Pennell

Daniel J Dairaghi

Eric Petajan

Cheng Ee

Krishna R Pattipati

J J Kim Wright

Shichang Xu

Penglie Zhang

Wei Yu Chen

Patrick Guy Haffner

Walter Willinger

Ajay Todimala

Matthew Roughan

Patrick Drew McDaniel

Vijay Gopalakrishnan

Jacobus Erasmus Van Der Merwe

Jin Wang

Sumeet Singh

Jeffrey Erman

Brian E McMaster

Yu Jin

Rajarajan Sivaraj

Pramod Jamkhedkar

Supratim Deb

Mehrdad Moradi

Amogh Dhamdhere

Rittwik Jana

Charles Robert Kalmanek, Jr

William A Aiello

William J Leighton, Iii

Mohammad Taghi Hajiaghayi

Dhruv Gupta

Bharath Balasubramanian

Mohammad Hossein Bateni

Yu Gu

Sanjay Rao

Kartikeya Chandrayana

Kittipat Apicharttrisorn

Theodore Karagioules

Zhuaqing Mao

Patrick Mcdaniel

Albert Gordon Greenberg

Balachander Krishnamurthy

Seungjoon Lee

Changhoon Kim

Zhengye Liu

Ganapathy Subramanian Sundaram

Vaneet Aggarwal

Christopher J Chase

Dongmei Wang

Dan Pei

Zhi-Li Zhang

Mithuna Shamabhat Thottethodi

Kiem-Phong Vo

William Christopher Fenner

Jeffrey Pang

Gopal N Kumar

Valeri Martichonok

Shankaranarayanan Puzhavakath Narayanan

J J Wright

Terani Nadadoor Vijaykumar

Ramesh Govindan

Shobha Venkataraman

Catherine R Loader

Jacobus E Van De Merwe

Bill Lin

Ashiwan Sivakumar

Yaguang Li

Zahaib Akhtar

Junxian Huang

Yu-Wei Sung

Oliver Spatschek

Jerry Chou

MohammadTaghi Hajiaghayi

Yihua Guo

Yan Chen

Anis Elgabli

Ruofan Jin

Qiang Xu

Andrew M Pennell

William J Leighton

Charles Robert Kalmanek

Brian E Mcmaster

Daniel Joseph Dairaghi

The technologies described herein are generally directed to modeling radio wave propagation in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include, for a network application, identifying, by a system comprising a processor, a characteristic value of a performance characteristic associated with an uplink connection enabled via a network of a user equipment to application server equipment hosting the network application. The method can further include, based on the characteristic value and a criterion, selecting, by the system, a first packet size for the uplink connection. The method can further include communicating, by the system, to the user equipment, the first packet size for use with the uplink connection.

Streaming augmented reality data in a fifth generation (5G) or other next generation network

A method includes acquiring a playlist identifying a plurality of video files to be played back during a video streaming session on an endpoint device, obtaining, from an operator of a communications network over which the video files are to be downloaded, a maximum throughput for the video streaming session, selecting a subsequent video file that is scheduled in the playlist for playback after a playback of a currently playing video file, wherein the subsequent video file includes a plurality of chunks, selecting, based on the maximum throughput and for each of the chunks, a variant, such that a plurality of variants is selected in which each variant corresponds to one chunk of the plurality of chunks, wherein the variants are selected to maximize a utility function that is constrained by the maximum throughput, and downloading the plurality of variants to a local buffer of the endpoint device.

Optimization of bitrate adaptation and prefetching for short-form video

A method includes acquiring a playlist identifying video files and an order in which the video files are to be played back during a video streaming session on an endpoint device, obtaining, from an operator of a communications network over which the video files are to be downloaded, a maximum value of a streaming parameter for the video streaming session, selecting a subsequent video file that is scheduled for playback after a playback of a currently playing video file, wherein the subsequent video file includes a plurality of chunks, selecting, for each chunk, a variant, such that a plurality of variants is selected in which each variant corresponds to one chunk of the plurality of chunks, wherein the selecting the variant is based on both the maximum value and a measured value for the streaming parameter, and downloading the plurality of variants to a local buffer of the endpoint device.

Bitrate adaptation and prefetching for short-form video

A processing system may obtain a downscaled version of a reference copy of a video, comprising a plurality of downscaled versions of a plurality of frames of the reference copy of the video, obtain a first recorded frame of a first variant of a plurality of variants associated with the reference copy of the video, where the plurality of variants comprises a plurality of copies of the video encoded at different bitrates, generate a first downscaled version of the first recorded frame, calculate a first plurality of image distances between the first downscaled version of the first recorded frame and the plurality of downscaled versions of the plurality of frames of the reference copy of the video, and determine a first frame index of the first recorded frame in accordance with a first least image distance from among the first plurality of image distances that is calculated.

Adaptive bitrate video testing from screen recording

Systems and methods provide containers instantiated for each user equipment (UE), or on 'per-UE' bases, which consolidate certain network functions for processing UE traffic into an efficient, in-network, and proximate virtualization to reduce latency and increase customizability.

Customizable and low-latency architecture for cellular core networks

Devices, computer-readable media, and methods for making a cache admission decision regarding a video chunk are described. For instance, a processing system including at least one processor may obtain a request for a first chunk of a first video, determine that the first chunk is not stored in a cache, and apply, in response to the determining that the first chunk is not stored in the cache, a classifier to predict whether the first chunk will be re-requested within a time horizon, where the classifier is trained in accordance with a set of features associated with a plurality of chunks of a plurality of videos. When it is predicted via the classifier that the first chunk will be re-requested within the time horizon, the processing system may store the first chunk in the cache.

Adaptive bitrate video cache

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.

Methods, systems, and devices for streaming video content according to available encoding quality information

Various embodiments disclosed herein provide for identifying optimal data packet size to achieve a higher throughput a wireless communication network. According to some embodiments, a system can comprise monitoring a transmit control protocol performance associated with a first transmission of data packets over a first duration of time, wherein a packet size of the data packets is a first data packet size, detecting that the transmit control protocol performance satisfies a function with respect to a threshold and in response to the detecting that transmit control protocol performance satisfies the function with respect to the first threshold, determining a second data packet size to use for a second transmission of the data packets over a second duration of time, transmitting a request to change the packet size of the data packets to the second data packet.

Dynamic packet size adaptation to improve wireless network performance for 5G or other next generation wireless network

Aspects of the subject disclosure may include, for example, accessing adaptive streaming information for a multimedia content segment, determining available access bandwidths for a plurality of video tracks and a plurality of audio tracks identified by the adaptive streaming information, selecting one of a plurality of candidate track pairings identified by the adaptive streaming information based on the available access bandwidths, obtaining video content of the multimedia content segment via a video track of the selected track pairing, and obtaining audio content of the multimedia content segment via an audio track of the selected track pairing. Other embodiments are disclosed.

Adaptive streaming with demuxed audio and video tracks

A system includes one or more processors and a memory. The processor(s) effectuates operations including receiving a query, wherein the query identifies one or more problems in the network. The processor(s) further effectuates operations including retrieving contextual information and problem information, associated with the one or more problems, from a knowledge base and generating a first recommendation list comprising one or more recommendations, wherein each of the one or more recommendations comprises the contextual information or the problem information and at least one course of action. The processor(s) further effectuates operations including receiving a selection of a recommendation from the first recommendation list and updating the knowledge base to include information associated with the selection of the recommendation and generating, in response to a further query, a second recommendation list comprising one or more further recommendations that include further contextual information or further problem information retrieved from the knowledge base.

Network troubleshooting digital assistant system

Aspects of the subject disclosure may include, for example, a method in which a processing system parses a network trace to collect packet information for an encrypted adaptive bite rate (ABR) video stream encoded into a plurality of tracks; detects request packets corresponding to a sequence of requests for video segments to be downloaded at a network client; and determines a traffic volume downloaded at the network client to obtain a sequence of traffic volumes. The processing system identifies, for each of the sequence of traffic volumes, a set of candidate segments each having a size meeting a size-matching criterion; selects a segment from the set of candidate segments to determine a segment sequence meeting an index-matching criterion; and infers characteristics of the sequence of traffic volumes based on the segment sequence. Other embodiments are disclosed.

Method and apparatus for inferring ABR video streaming behavior from encrypted traffic

A processing system including at least one processor may obtain a selection of a desired perceptual quality for a video and selects a first video chunk from among a first plurality of video chunks, wherein the first plurality of video chunks is associated with a first time block of the video, wherein the selecting is based upon a manifest file of the video, wherein each video chunk of the first plurality of video chunks is associated with a respective perceptual quality and a respective encoding bitrate, wherein the first video chunk is part of a subset of the first plurality of video chunks for which the respective perceptual quality matches the desired perceptual quality within a predefined threshold tolerance, and wherein the respective encoding bitrate of the first video chunk is lower than a highest encoding bitrate associated with the subset of the first plurality of video chunks. The processing system may obtain the first video chunk from a server and store the first video chunk in a buffer.

Chunk-based filtering to optimize video streaming quality and data usage

Growing community of inventors

Chatham, NJ, United States of America

Subhabrata Bapi Sen