Date & Time:
January 21, 2020 3:00 pm – 4:00 pm
Crerar 298, 5730 S. Ellis Ave., Chicago, IL,
01/21/2020 03:00 PM 01/21/2020 04:00 PM America/Chicago Tarun Mangla (Georgia Tech) – Video QoE Estimation Using Network Measurement Data Crerar 298, 5730 S. Ellis Ave., Chicago, IL,

Video QoE Estimation Using Network Measurement Data

More than ever before, last-mile Internet Service Providers (ISPs) are forced to efficiently provision and manage their networks to meet the growing demand for Internet video. This network optimization requires ISPs to have an in-depth understanding of end-user video Quality of Experience (QoE). However, understanding video QoE is challenging for ISPs as they generally do not have access to applications at end-user devices. Instead, they rely on measurements of network traffic to estimate objective QoE metrics. This is challenging due to the complex relationship between the network observable data and the video QoE metrics resulting from HTTP-based Adaptive Streaming (HAS) mechanisms; these mechanisms provide robustness to short-term variations in the underlying network conditions by using a video buffer and bitrate adaptation.

In this talk, I will present methods that enable ISPs to infer video QoE from passive network measurements. Our developed methods model a video session based on the network traffic dynamics of the HAS protocol; thus, making them fairly generalizable and minimally dependent on ground truth QoE metrics. I will first describe MIMIC, a session modeling-based approach to infer QoE for unencrypted video. I will then describe how we extend MIMIC to infer QoE for encrypted video using packet traces. Finally, I will describe VideoNOC, a video QoE inference system for cellular ISPs. In designing VideoNOC, we address system challenges to measure video QoE inside a cellular ISP, arising largely because of the scale of the network traffic and the complex cellular network architecture. VideoNOC is currently deployed inside a major cellular operator in the US.

Host: Nick Feamster

Tarun Mangla

PhD Student, Georgia Institute of Technology

Tarun Mangla is a PhD student in the School of Computer Science at the Georgia Institute of Technology, co-advised by Mostafa Ammar and Ellen Zegura. His research interests span video streaming, network measurements, and cellular networks. He completed his bachelors in Computer Science and Engineering from Indian Institute of Technology, Delhi (2014) and MS in Computer Science from Georgia Tech (2018). He is a recipient of the Best Paper Award at IFIP TMA, 2018.

Related News & Events

UChicago CS News

Five UChicago CS students named to Siebel Scholars Class of 2024

Oct 02, 2023
UChicago CS News

UChicago Computer Scientists Bring in Generative Neural Networks to Stop Real-Time Video From Lagging

Jun 29, 2023
UChicago CS News

UChicago Team Wins The NIH Long COVID Computational Challenge

Jun 28, 2023
UChicago CS News

UChicago Assistant Professor Raul Castro Fernandez Receives 2023 ACM SIGMOD Test-of-Time Award

Jun 27, 2023
UChicago CS News

Computer Science Displays Catch Attention at MSI’s Annual Robot Block Party

Apr 07, 2023
UChicago CS News

Asst. Prof. Rana Hanocka Receives NSF Grant to Develop New AI-Driven 3D Modeling Tools

Feb 28, 2023
UChicago CS News

Professor Heather Zheng Named ACM Fellow

Jan 18, 2023
Two students looking at a wearable device
UChicago CS News

High School Students Find Their Place in Computing Through Wearables Workshop

Jan 13, 2023

Ian Foster – Better Information Faster: Programming the Continuum

Jan 06, 2023
UChicago CS News

Q&A: Ian Foster on Receiving the 2023 IEEE Internet Award

Jan 06, 2023
UChicago CS News

Professor Fred Chong Named IEEE Fellow

Dec 09, 2022
UChicago CS News

Associate Professor Diana Franklin Named ACM Distinguished Member

Dec 07, 2022
arrow-down-largearrow-left-largearrow-right-large-greyarrow-right-large-yellowarrow-right-largearrow-right-smallbutton-arrowclosedocumentfacebookfacet-arrow-down-whitefacet-arrow-downPage 1CheckedCheckedicon-apple-t5backgroundLayer 1icon-google-t5icon-office365-t5icon-outlook-t5backgroundLayer 1icon-outlookcom-t5backgroundLayer 1icon-yahoo-t5backgroundLayer 1internal-yellowinternalintranetlinkedinlinkoutpauseplaypresentationsearch-bluesearchshareslider-arrow-nextslider-arrow-prevtwittervideoyoutube