摘要 I
Abstract II
目錄 III
表目錄 V
圖目錄 VI
第一章 簡介 1
1.1 研究背景與動機 1
1.2 論文架構 3
第二章 文獻探討 4
2.1 軟體定義網路 4
2.2 網路功能虛擬化 6
2.3 網路切片 8
2.3.1 5G與網路切片 10
2.3.2 後端服務Server與網路切片 10
2.4 深度學習Deep learning 14
2.4.1 Tensorflow 14
2.4.2 Multilayer perceptron 15
2.4.3 Convolutional Neural Network 15
2.4.4 Recurrent Neural Network 15
2.4.5 Long Short-Term Memory 15
2.5 網路切片之資源分配與流量預測 16
第三章 網路切片實驗環境架設 18
3.1 VMware ESXi 18
3.2 OpenWrt 20
3.3 Open vSwitch 20
3.4 網路聚合 21
3.4.1 Bonding Mode 21
3.4.2 網路切片中的網路聚合 22
3.5 OpenWrt上的OVS Meter 23
3.6 以DSCP分類網路切片 23
3.7 環境架設結果 25
第四章 網路切片之動態資源分配 29
4.1 網路切片之網路資源動態分配 29
4.1.1 動態分配轉發封包路由 29
4.1.2 轉發埠的資源分配 33
4.2 網路切片之運算資源動態分配 37
4.2.1 VMware Powercli 38
4.2.2 轉發流量與運算資源分析 39
4.3 差異化服務(DiffServ) 40
4.4 實驗結果與分析 45
第五章 網路流量預測 53
5.1 網路流量預測之深度學習模型訓練資料收集 53
5.1.1 Live Stream訓練資料蒐集工具 54
5.1.2 Buffering Video訓練資料收集 57
5.2 網路流量預測之深度學習模型分析 58
5.2.1 Live Stream網路流量深度學習模型預測分析 58
5.2.2 Buffered video網路流量深度學習模型預測分析 66
5.3 以深度學習模型即時預測網路流量 74
5.3.1 Live Stream網路流量即時預測 74
5.3.2 Buffered Video網路流量即時預測 78
第六章 結論與未來研究方向 82
參考文獻 84
附錄A 88
附錄B 90
附錄C 96

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