臺灣博碩士論文加值系統

根據網路發展趨勢推估，未來網路資料流量的大幅成長，將會造成許多服務無法使用的窘境，原因在於受限的網路頻寬以及傳輸協定，為解決上述問題，學者們紛紛研究並提出了新的傳輸架構，內容核心網路(Content Centric Network, CCN)，是其中解決的方式之一，藉由以資料為基礎的網路方式取代現有的IP位址為基礎的傳輸方式，使用資料命名的特點和內容暫存的技術來改善整體網路傳輸效能，但是目前發展尚未穩定的資料快取機制，將會在傳輸路徑所經過的每個路由器中都快取資料，此方式會造成記憶空間的浪費，也壓縮了其他種類資料的儲存空間，因此如何有效地作快取節點的選擇，成為了此研究熱門討論的議題之一。
本研究將提出新的快取機制，藉由計算並給予用戶端到資料存放處路徑經過的各路由器一權重值，根據權重值作快取節點的選擇，以降低各用戶端取得資料所經過路徑的平均跳數為主要目標，並同時減少路由器快取資料的數量，解決一般快取節點選擇方式所造成的網路空間浪費和傳輸效率不佳的問題，如此一來便能更靈活的運用網路空間資源，提高網路傳輸的效能，文中使用ndnSIM模擬軟體，模擬提出機制在內容核心網路中與傳統方法進行比較，結果顯示提出方法確實改善傳統快取機制所造成的問題，提高整體網路傳輸的效率。

According to the trend of network development, estimates that future data traffic grew. The dilemma will cause many services cannot be used due to limited network bandwidth and the transfer protocol. In order to solve the above problem, scholars have studied and proposed new transport architecture, and Content Centric Network (CCN) is one way to solve. Through data-based network to replace the existing IP address-based transmission. Using name data and content cache to improve network performance, but the data cache scheme is not stable yet. This will result in a waste of memory space, and compression of the other types of data storage space. Therefore cache node selection has become one of the hot topics.
This research will present a new cache scheme, by calculating and give the client to the data repository path through router a weight value, and the choice of weights for the cache node. To reduce the client to obtain data the average hop count as its main objective, and at the same time reduces the number of router cache data. So can resolve the current caching scheme caused by the problem of waste and poor efficiency of internet space. This can provide greater flexibility in the use of space resources, and increasing the effectiveness of network transmission. In this paper we use the ndnSIM simulation of the proposed scheme compared with traditional methods. Result display proposed scheme improve the problems posed by the traditional caching scheme, and increase overall network efficiency.

摘要 i
ABSTRACT ii
致謝 iii
Contents iv
Chapter 1 Introduction 1
1.1 Introduction of Content Centric Network 1
Chapter 2 Background 3
2.1 Content Centric Network 3
2.2 Content Cache of Content Centric Network 4
2.3 Related Works 5
Chapter 3 Problem Definition 6
3.1 Problem Description 6
3.2 Cache Scheme based on Average Hop 8
3.3 CCN Example Scenario 11
3.4 AH Example Scenario 11
Chapter 4 Performance Evaluation 13
4.1 Simulation Settings 13
4.2 Simulation Results 14
Chapter 5 Conclusions and Future Works 20
Reference 21

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