進階搜尋


 
系統識別號 U0026-0812200914080846
論文名稱(中文) 基於決策樹的快速二分搜索封包分類法
論文名稱(英文) Fast Binary Search Packet Classification Based On Decision Trees
校院名稱 成功大學
系所名稱(中) 資訊工程學系碩博士班
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 96
學期 1
出版年 97
研究生(中文) 羅偉恩
研究生(英文) Wei-En Lo
電子信箱 p7694154@mail.ncku.edu.tw
學號 p7694154
學位類別 碩士
語文別 英文
論文頁數 29頁
口試委員 口試委員-謝孫源
口試委員-李同益
口試委員-朱治平
指導教授-張燕光
口試委員-蘇銓清
中文關鍵字 封包分類  決策樹  二分搜尋法 
英文關鍵字 Packet Classification  Decision Tree  Binary Search 
學科別分類
中文摘要 隨著網路需求的快速成長以及網路應用程式的出現,現今的骨幹路由器需要在短時間內將封包分類成各個串流。在這篇論文中,我們提出了一個新的演算法-快速二分搜索封包分類法-以增進搜尋速度及記憶體空間的使用效率。在我們的演算法當中,我們先利用決策樹將分類規則表進行切割,然而在搜尋上,我們使用二分搜尋法來取代傳統遍歷樹的查找方式。我們使用一種基於湊雜的位元選擇策略來代替以往的值域切割法,以降低不平衡環境對記憶體使用率造成的衝擊。我們的演算法可以被實作在兩種不同的架構。可變位元選擇架構在不同節點上,可以選擇任意作為切割的位元,而擁有較好的記憶體使用率;固定位元選擇架構在相同層級的節點上選擇相同的切割位元,以降低封包編碼時間,增進搜尋速度。在最後,我們將演算法與另二個知名的演算法─HiCuts及HyperCuts演算法─作比較。可變位元選擇架構在各種分布的分類規則表中,都能有較好的效能;固定位元選擇架構在均勻分佈的規則表中,效能比HiCuts高出20%以上,而在不平衡的環境中甚至能高出50%。
英文摘要 With the rapid growth of internet requirement and the occurrence of network applications, backbone routers nowadays need to classify packets into flows in a short time. In this paper, we propose a new algorithm called fast binary search packet classification to improve the efficiency on both search speed and the memory storage. In our algorithm, we first partition the filter table with decision tree but process a binary search on leaf nodes instead of the traditional tree traversal. We use a hash- based bit selecting strategy to replace the range cutting method in order to reduce memory usage and the impact caused by unbalance environment. Our algorithm can be implemented in two schemes. Variable-selected-bit scheme chooses different bit on each node and thus has better memory utilization. Fixed-selected-bit scheme chooses same bit on each node in the same level in order to reduce the packet encoding time and then increase the search speed. At last we compare our algorithm with two well-known algorithm - HiCuts and HyperCuts. Result shows that variable- selected-bit scheme has better performance on memory usage in all kinds of filter tables than others; another fixed-selected-bit scheme performs 20% better than HiCuts on search in filter tables with uniform distribution and even more than 50% better in an unbalance environment.
論文目次 Chapter 1 Introduction 1
Chapter 2 Related Work 3
2.1 Some of the Packet Classification Technique 3
2.2 Packet Classification based on Decision Tree 4
2.2.1 HiCuts Algorithm 4
2.2.2 HyperCuts Algorithm 5
2.3 Packet Classification with Hardware Support 7
Chapter 3 Proposed Scheme 9
3.1 Idea and Basic Concept 9
3.1.1 Binary Search 9
3.1.2 Bit-Selecting Strategy 12
3.2 Variable-Selected-Bit Scheme 15
3.3 Fixed-Selected-Bit Scheme 17
Chapter 4 Experimental Result 21
Chapter 5 Conclusion 27
Reference 28
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