Modeling streaming QoE in wireless networks with large-scale measurement of user behavior

Zhujun Xiao, Yuedong Xu, Hui Feng, Tao Yang, Bo Hu, Yipeng Zhou

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

6 Citations (Scopus)

Abstract

Unraveling quality of experience (QoE) of video streaming is very challenging in bandwidth shared wireless networks. It is unclear how QoE metrics such as buffering time and starvation behavior interact with dynamics of streaming traffic load. In this paper, we collect view records from one of the largest streaming providers in China over two weeks and perform an in-depth measurement study on flow arrival and viewing time that shed light on realistic streaming traffic pattern. Our most important observation is that the viewing time of streaming users fits a hyper-exponential distribution quite well. This implies that all the videos can be categorized into two classes, short and long viewing time with separated time scales. We then map the traffic pattern of large-scale measurement to bandwidth sharing cellular networks. We propose two models to compute the close-form starvation probability and mean sojourn time on the basis of ordinary differential equations (ODEs). Extensive trace-driven simulations validate their accuracy. The proposed models precisely capture how the QoE metrics of video streaming in each class are influenced by the scheduling algorithms at a base station.
Original languageEnglish
Title of host publication2015 IEEE Globecom Workshops
Subtitle of host publicationProceedings
PublisherIEEE:Institute of Electrical Electronics Engineers Inc
Pages1-6
Number of pages6
ISBN (Electronic)9781479959525
ISBN (Print)9781467395267
DOIs
Publication statusPublished - 2015
Externally publishedYes

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