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系統識別號 U0026-1106202016411700
論文名稱(中文) 考慮基地台和行動邊緣計算伺服器換手的QoE導向MPEG-DASH影片串流服務
論文名稱(英文) QoE-driven Bitrate Adaption for MPEG-DASH Video Streaming Considering the BS and Mobile Edge Computing (MEC) Server Handoff
校院名稱 成功大學
系所名稱(中) 資訊工程學系
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 108
學期 2
出版年 109
研究生(中文) 胡子源
研究生(英文) Zi-Yuan Hu
學號 P76071488
學位類別 碩士
語文別 英文
論文頁數 84頁
口試委員 指導教授-黃崇明
口試委員-蔡孟勳
口試委員-謝錫堃
口試委員-黃仁竑
口試委員-童曉儒
中文關鍵字 HTTP自適應影音串流(HAS)  MPEG-DASH  移動邊緣計算(MEC)  頻寬預測  自適應調整影片畫質  MEC服務器換手  影音串流換手 
英文關鍵字 HTTP adaptive video streaming (HAS)  MPEG-DASH  Mobile Edge Computing (MEC)  bandwidth prediction  video bitrate adaption  MEC Server Handoff  Streaming Handoff 
學科別分類
中文摘要 本論文提出了基於移動邊緣計算(MEC)協助MPEG-DASH來進行HTTP自適應影音串流的服務,及考慮穩定度的畫質調整和MEC伺服器換手的控制方案。在所提出的方法中,MEC伺服器在無線行動網絡中扮演計算和緩存機制的角色。為了使MEC伺服器計算出較合適的畫質決策,本論文提出的方法包含(i)使用自適應濾波器估計使用者裝置的頻寬,(ii)透過估計的頻寬和APP回報的緩衝區情況,且(iii)考慮影片畫質的穩定性,從而選擇較合適的畫質。本論文的方法不僅考慮(i)使用者頻寬和緩衝區問題,還考慮(ii)自適應串流的長期和短期畫質變化。假定在一個MEC服務器與一個BS相聯的系統中,若使用者移動的話,可能會有換手連接的4G / 5G基站(BS),這導致MEC伺服器也會切換。因此,本論文提出BS / MEC伺服器換手的控制方案,可以使MEC伺服器切換時的畫質更加流暢。本論文提出的方法在4G LTE網絡環境中實現,使用Linux系統和USRP設備(實驗室規模的eNB系統)構建。根據實驗結果,提出的方法能提升對於無線行動網絡中的MPEG-DASH串流的影片畫質穩定度,包含在MEC服務器換手處理期間。
英文摘要 This thesis proposed the Mobile Edge Computing (MEC)-based video streaming with quality-aware video bitrate adaption and MEC server handoff control schemes using the MPEG-DASH video streaming architecture. Using the proposed method, the MEC sever plays the role of both computing and caching mechanisms in the remote video server-edge server-client 3-tier video streaming platform over the wireless mobile network. In this work, the proposed quality-aware video bitrate adaption and MEC server handoff control schemes are used to assist the MPEG-DASH video streaming. To calculate the video bit rate for each video segment of the MPEG-DASH video streaming, the proposed method (i) has the estimated bandwidth using the adaptive filter mechanism, (ii) derives some candidate video bit rates by considering the estimated bandwidth and the buffer occupancy situation in the client side, which was reported from the User APP, and then (iii) selects a video bit rate from the candidate ones considering video quality’s stability. For the video quality’s stability concern, the proposed method considered not only (i) both bandwidth and buffer issues but also (ii) the long-term quality variation and the short-term quality variation to have the adaptive video streaming. Since the user is moving, the attached 4G/5G Base Station (BS) can be changed, i.e., the BS handoff can happen, which results in the MEC server handoff, for which it is assumed that one MEC server is associated with one BS in this work. Thus, this work proposed the BS/MEC server handoff control scheme to make the playing quality smoother when the MEC server handoff happens. The proposed method has been implemented in the experimental 4G LTE network, which was built using the Linux system and the USRP device, which is a lab-scaled eNB system. The results of the performance evaluation shown that the proposed method has the more stable video quality, including during the MEC server handoff processing period, for the MPEG-DASH video streaming over the wireless mobile network.
論文目次 中文口委簽名 I
英文口委簽名 II
摘要 III
Abstract IV
誌謝 VI
Contents VII
List of Figures IX
List of Table XIII
Chapter 1 Introduction 1
Chapter 2 Preliminaries 6
2.1. Adaptive Filter 6
2.2. Recursive Least Square (RLS) Algorithm 7
Chapter 3 Related Works 12
3.1. MEC server Assisted Video Streaming 12
3.2. Video Bitrate Adaption 13
3.3. Bandwidth Prediction 14
3.4. Streaming Handoff 15
3.5. MEC server Handoff 16
Chapter 4 The Architecture and Functional Scenario 18
4.1. Architecture 18
4.2. The Functional Scenarios 19
Chapter 5 The Proposed Control Method 25
5.1. The RLS-based Bandwidth Prediction (RBP) Scheme 25
5.2. The Bandwidth Assisted Buffer-based Bitrate Adaptation (BBA) Control Scheme 29
5.3. The Quality-Adjustment Scoring (QAS) Scheme 35
5.4. The MEC Service Handoff Scheme 39
Chapter 6 Performance Evaluation 47
6.1. The Experimental Environment 47
6.2. The Compared Methods and Evaluation Metrics 49
6.3. Performance Results 53
Chapter 7 Conclusion 79
Bibliography 80
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