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Appl."],"published-print":{"date-parts":[[2018,4,30]]},"abstract":"<jats:p>\n            The large share of traffic in the Internet generated by video streaming services puts high loads on access and aggregation networks, resulting in high costs for the content delivery infrastructure. To reduce the bandwidth consumed while maintaining a high playback quality, video players use policies that control and limit the buffer level by using thresholds for pausing and continuing the video download. This allows shaping the bandwidth consumed by video streams and limiting the traffic wasted in case of playback abortion. Especially in mobile scenarios, where the throughput can be highly variant, the buffer policy can have a high impact on the probability of interruptions during video playback. To find the optimal setting for the buffer policy in each network condition, the relationship between the parameters of the buffer policy, the network throughput dynamics, and the corresponding video playback behavior needs to be understood. To this end, we model the video buffer as GI\/GI\/1 queue with\n            <jats:italic>pq<\/jats:italic>\n            -policy using discrete-time analysis. By studying the stochastic properties of the buffer-level distribution, we are able to accurately evaluate the impact of network and video bitrate dynamics on the video playback quality based on the buffer policy. We find a fundamental relationship between the bandwidth variation and the expected interarrival time of segments, meaning that overproportionately more bandwidth is necessary to prevent stalling events for high bandwidth variation. The proposed model further allows to optimize the trade-off between the traffic wasted in case of video abortion and video streaming quality experienced by the user.\n          <\/jats:p>","DOI":"10.1145\/3183511","type":"journal-article","created":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T12:22:17Z","timestamp":1524658937000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["A Generic Approach to Video Buffer Modeling Using Discrete-Time Analysis"],"prefix":"10.1145","volume":"14","author":[{"given":"Valentin","family":"Burger","sequence":"first","affiliation":[{"name":"University of W\u00fcrzburg, W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Zinner","sequence":"additional","affiliation":[{"name":"University of W\u00fcrzburg, W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lam","family":"Dinh-Xuan","sequence":"additional","affiliation":[{"name":"University of W\u00fcrzburg, W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florian","family":"Wamser","sequence":"additional","affiliation":[{"name":"University of W\u00fcrzburg, W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phuoc","family":"Tran-Gia","sequence":"additional","affiliation":[{"name":"University of W\u00fcrzburg, W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,4,25]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"SPIE Optical Engineering+Applications","author":"Adzic Velibor","unstructured":"Velibor Adzic , Hari Kalva , and Borko Furht . 2011. 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