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A Simple Model for Predicting the Number and Duration of Rebuffering Events for YouTube Flows

A Simple Model for Predicting the Number and Duration of Rebuffering Events for YouTube Flows. Author: Pablo Ameigeiras, Alba Azcona-Rivas, Jorge Navarro-Ortiz, Juan J. Ramos-Mu˜noz, and Juan M. L´opez-Soler Sperker:MA2G0101 林韋呈. OUTLINE. INTRODUCTION

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A Simple Model for Predicting the Number and Duration of Rebuffering Events for YouTube Flows

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  1. A Simple Model for Predicting the Number and Duration ofRebuffering Events for YouTube Flows Author:Pablo Ameigeiras, Alba Azcona-Rivas, Jorge Navarro-Ortiz, Juan J. Ramos-Mu˜noz, and Juan M. L´opez-Soler Sperker:MA2G0101 林韋呈

  2. OUTLINE • INTRODUCTION • OVERVIEW OF A REBUFFERING EVENT DURINGPLAYBACK • EXPERIMENTAL SETUP • SIMPLE PROCEDURE FOR OBTAINING THE DURATIONOF A REBUFFERING EVENT • EXAMPLE OF THE USE OF THE REBUFFERING MODEL • CONCLUSIONS

  3. Introduction • 網路流量的龐大的成長 • Progressive download 技術 • Buffer的目的是為了減少http/tcp傳輸的延遲

  4. Introduction • 使用者對於Http視訊串流品質的評估實驗(QoE)，顯示對於平均rebuffering的時間有強烈的相依性 • 提出一個預測YouTube的progressive downloads效能只標的Simple Model

  5. OVERVIEW OF A REBUFFERING EVENT DURINGPLAYBACK • B(t)只要持續的成長Rr(t)就會持續的大於Vr(t) • 頻寬不夠時B(t)就會持續地減少 • 當B(t)不夠時中斷播放開始rebuffering

  6. OVERVIEW OF A REBUFFERING EVENT DURINGPLAYBACK 𝛽≈0.5s

  7. EXPERIMENTAL SETUP • 由PC連接校內區網，有連到網際網路 • 使用YouTubeplayer的API，JavaScript和Java Servlet監視網頁收集數據 • Launcher 的Servlet配置透過SoftPerFect來降低平寬降至Vr(t)的75%

  8. EXPERIMENTAL SETUP • 𝛿𝑖𝑗 表示𝛿 在地i個下載的video clip中的第j個rebufferingenent , i

  9. EXPERIMENTAL SETUP • 𝛿取中值約等於1.85

  10. EXPERIMENTAL SETUP • 平均的錯誤估計值約等於0.07s , i

  11. SIMPLE PROCEDURE FOR OBTAINING THE DURATIONOF A REBUFFERING EVENT

  12. EXAMPLE OF THE USE OF THE REBUFFERING MODEL • Rebuffering model 透過一個LTE模擬器實作 • 使用者請求下載一個120秒的Vedio clip • 其中Vr(t)假設一個值 • 𝛽 = 0.5s and 𝛿 =1.85s.

  13. EXAMPLE OF THE USE OF THE REBUFFERING MODEL • 網路模擬器提供Rr(t)，基於radio link的傳輸速度，基於每個使用者傳輸狀況計算Geometry Factor

  14. CONCLUSIONS • 本論文提出一個，預測在從YouTube progressivedownloads期間的rebuffering事件的數量的 simple model，此model有兩個thresholds，𝛽 ≈ 0.5𝑠，透過實驗結果得到 𝛿 ≈ 1.85𝑠，錯誤估計值約0.17s在CDF的95th percentile

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