Diagonal tuple space search in two dimensions

Due to the evolution of the Internet and its services, the process of forwarding packets in routers is becoming more complex. In order to execute the sophisticated routing logic of modern firewalls, multidimensional packet classification is required. Unfortunately, the multidimensional packet classification algorithms are known to be either time or storage hungry in the general case. It has been anticipated that more feasible algorithms could be obtained for conflict-free classifiers. This paper proposes a novel two-dimensional packet classification algorithm applicable to the conflict-free classifiers. It derives from the well-known tuple space paradigm and it has the search cost of Ο(log w) and storage complexity of Ο(n2w log w), where w is the width of the protocol fields given in bits and n is the number of rules in the classifier. This is remarkable because without the conflict-free constraint the search cost in the two-dimensional tuple space is Θ(w)

Diagonal Tuple Space Search in Two Dimensions

Abstract. Due to the evolution of the Internet and its services, the process of forwarding packets in routers is becoming more complex. In order to execute the sophisticated routing logic of modern firewalls, multidimensional packet classification is required. Unfortunately, the multidimensional packet classification algorithms are known to be either time or storage hungry in the general case. It has been anticipated that more feasible algorithms could be obtained for conflict-free classifiers. This paper proposes a novel two-dimensional packet classification algorithm applicable to the conflict-free classifiers. It derives from the well-known tuple space paradigm and it has the search cost of Ο(log w) and storage complexity of Ο(n2 w log w), where w is the width of the protocol fields given in bits and n is the number of rules in the classifier. This is remarkable because without the conflict-free constraint the search cost in the twodimensional tuple space is Θ(w)

A Fast Packet Classification Algorithm using Diagonal Tuple Space Search

由於網路速度的不斷提升，網路的應用與服務也日益增加。如何提供有效率的品質服務(QoS)便成為重要課題，而提供適當的品質服務時必須做有效率的封包分流(Flow Classification)。 本論文主要在探討如何提供一個有效率的封包分流機制，在一般的網路應用上主要針對來源位址以及目標位址做二維的分流，並且透過一些例外處理來確保搜尋的正確性。 本論文使用對角線同時包含行以及列的特性，並且將原先在元素空間搜尋方法中使用到的標記以及預先計算做到更強的功用，使二維的元素空間搜尋時間從O (log 2 n ) 變為 O (log n )，更針對固定的元素空間以及動態的元素空間造成的效能影響做了比較。在本文的末端做了相關研究與本方法的數學複雜度分析比較，並且透過模擬來驗證本方法的效能與其他之比較。As the network speed grows, we have witnessed the widespread of the applications and services over the Internet. As the result, how to provide a quality of services (QoS) scheme effectively has become an important issue. The first step to support QoS would be to offer an efficient flow classification scheme. In this thesis, we discuss how to provide an efficient flow classification based on source and destination IP addresses, i.e., two-dimensional flow classifications for the general application in the Internet. In addition, we devise a procedure to process exceptions in order to make sure that the search result is correct. The proposed scheme, Diagonal Tuple Space Search (DTSS), employs the characteristics of a matrix, which has the element in the diagonal form. With the help of pre-computation and marker, we can effectively reduce the search time without incurring excessive memory usage. The search time complexity can be decreased from O (log 2 n) to O (log n) by using this algorithm. We compare different DTSS with fixed tuple space and dynamic tuple space. We then compare the performance of our approaches with the related work in the literature by ways of mathematical analysis and confirm the results with simulation. It is shown that our approaches obtain better search time complexity and memory consumption.論文摘要 2 Abstract 3 目錄 4 圖表目錄 5 第一章、緒論 7 1.1 簡介 7 1.2 研究動機 8 1.3 論文架構 8 第二章、問題描述與相關研究 9 2.1 問題描述 (Problem descriptions) 9 2.2 相關研究 (Related Work) 11 2.2.1 Ternary CAM 11 2.2.2 Linear Search 11 2.2.3 Grid of Trie 11 2.2.4 Tuple Space Search 12 2.2.5 Rectangle Search 13 2.2.6 Two-dimensional Binary Tuple Space Search 15 2.3 相關研究比較 17 第三章、對角化元素空間搜尋機制介紹 18 3.1對角化元素空間(Diagonal Tuple Space)建構方式 18 3.2標記以及預先計算之功能與建構方式 21 3.3 對角化元素空間搜尋演算法之流程 25 3.4 規則搜尋方式 26 3.5 搜尋盲點與解決方式 27 第四章、數學時間複雜度以及模擬結果分析 31 4.1數學時間複雜度分析與比較 31 4.2 模擬結果，分析，以及比較 33 第五章、結論與未來展望 41 參考文獻 4