隨著網際網路的進一步發展，現今大多都被高速和與影像相關的服務所佔據，下一代網路將對ISP的網路進行優化。美國國家科學基金計畫提出了新的網路架構Named Data Network（NDN），建立網路資料暫存和基於內容命名的路由機制，來降低傳輸流量、加快相應速度。
本論文將以NDN的架構，提出合適NDN的QoS方法，針對NDN網路中不同類型資料做QoS分類，導入IP封包逾時即丟棄的存活時間(Time To Life, TTL)概念，取代傳統記憶體更新方式-先進先出演算法(FIFO)及最久沒有使用演算法（LRU），給予不同的存活時間，資料在來源端時先做分類，定義各種資料在暫存器中的存活時間，降低路由器暫存器(Content Store, CS)的負載量，在不增加服務延遲時間的前提下，使NDN網路的建置得以減少大量記憶體建置成本，在低網路傳輸的狀況下，減少服務延遲。並且動態調整資料封包存活時間類型，以網路環境參數最佳化暫存時間的長度，最後模擬與驗證中，本論文提出的方法可以在低網路流量時，減少約莫15%服務延遲。

With the further development of the Internet, most of the network bandwidth has been now occupied by high-speed and image-related services, which will be extended to more mobile devices. To optimize transmission performance and enable the content distribution capabilities, the Next Generation Network (NGN) will focus on ISP optimization. For this reason, the Named Data Networking (NDN) project was founded by the U.S. National Science Foundation (NSF). The NDN project aims to enable automatic caching of data and develop a name-based routing mechanism to reduce the throughput and accelerate response time. 
Based on NDN architecture, this paper proposes a QoS enhancement method for NDN: QoS classification is made based on types of data and the concept of Time To Live (TTL), which indicates whether or not an IP packet has stayed in the network too long and should be discarded, is adopted to replace conventional memory update scheme, like the the Least Recently Used (LRU) algorithm. Our proposed method classifies data from the source and defines different TTL of different data types in the router register to reduce the load of the Content Store (CS). Without increasing the service delay, our proposed method helps NDN to decrease the memory construction cost and reduce the service delay under low throughput conditions. The simulation results prove that our proposed method reduces approximately 15% of service delay under low throughput conditions.

目   錄
圖目錄	VI
表目錄	VIII
第一章  緒論	- 1 -
1.1	前言	- 1 -
1.2	動機與目的	- 1 -
1.3	論文章節架構	- 3 -
第二章 背景知識與相關研究	- 4 -
2.1命名中心網路(Named Data Networking)	- 4 -
2.1.1 命名中心網路的架構	- 4 -
2.1.2命名中心網路封包	- 6 -
2.1.3 NDN路由器架構	- 8 -
2.1.4 NDN路由	- 10 -
2.1.5命名系統	- 16 -
2.1.6 NDN資料暫存庫	- 18 -
2.2 網路快取(Web Caching)	- 19 -
第三章 以資料封包存活時間改進命名中心網路之QoS機制	- 24 -
3.1  基於資料存活時間的NDN環境及架構	- 25 -
3.2  基於資料存活時間的NDN網路資料分級方式	- 27 -
3.3  基於資料存活時間的LRU封包置換方式	- 30 -
3.4  負載評估方式	- 32 -
3.5  基於封包存活時間的服務等待延遲預測	- 33 -
3.6  以馬可夫鏈評估存活時間改進	- 34 -
第四章 模擬環境與模擬結果分析	- 37 -
4.1  環境與參數設定	- 37 -
4.2  服務時間延遲比較	- 38 -
第五章 結論與未來展望	- 50 -
參考文獻	- 51 -


 
圖目錄
圖 2.1：網際網路與資料命名網路協定的沙漏模型比較	- 5 -
圖 2.2：IP網路封包架構	- 6 -
圖 2.3：NDN的封包架構	- 7 -
圖 2.4：NDN網路中節點架構	- 9 -
圖 2.5：NDN網路路由器興趣封包處理流程	- 13 -
圖 2.6：NDN網路路由器資料封包處理流程	- 14 -
圖 2.7：NDN網路整體路由示意圖	- 16 -
圖3.1：NDN 網路整體系統的架構	- 26 -
圖3.2：NDN 路由器記憶體配置	- 27 -
圖3.3：NDN 資料封包生命週期	- 32 -
圖3.4：資料生存時間改進馬可夫狀態轉移圖	- 36 -
圖4.1：模擬環境架構圖	- 38 -
圖4.2：情境資料組成圖	- 39 -
圖4.3：各實驗資料重複率(Repeat Rate)	- 39 -
圖4.4：LRU time vs network speed	- 40 -
圖4.5：TTL delay time vs network speed	- 41 -
圖4.6：網路速度對資料暫存庫大小關係	- 42 -
圖4.7：TTL 六個情境與LRU 負載比較	- 43 -
圖4.8：生存時間改進方法在 6種實驗下的服務延遲時間	- 44 -
圖4.9：平均(重複率5.34%) 生存時間改進與LRU服務延遲比較	- 45 -
圖4.10：低生存時間(重複率3.57%)生存時間改進&LRU服務延遲	- 46 -
圖4.11：低生存時間(重複率3.87%)生存時間改進&LRU服務延遲	- 46 -
圖4.12：中生存時間(重複率5.28%)生存時間改進&LRU服務延遲	- 47 -
圖4.13：長生存時間(重複率6.9%)生存時間改進&LRU服務延遲	- 47 -
圖4.14：長生存時間(重複率7.11%)生存時間改進&LRU服務延遲	- 48 -
圖4.15：資料新鮮度比較	- 49 -


 
表目錄
表3.1：資料類型與生存時間長度分類	- 29 -
表4.1：模擬參數表	- 37 -

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