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研究生:白書珉
研究生(外文):Shu-Min Pai
論文名稱:一個在軟體定義網路中基於FTRS演算法之高效率的流量聚合方法
論文名稱(外文):An Efficient Flow-aggregation Scheme Based on FTRS Algorithm in SDN
指導教授:林偉林偉引用關係
口試委員:許蒼嶺王國禎黃秋煌王丕中
口試日期:2017-07-04
學位類別:碩士
校院名稱:國立中興大學
系所名稱:資訊工程學系所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:31
中文關鍵詞:流量聚合OpenFlow交換器軟體定義網路
外文關鍵詞:Flow aggregationOpenFlow switchSDN
相關次數:
  • 被引用被引用:0
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  • 收藏至我的研究室書目清單書目收藏:2
軟體定義網路(SDN)近幾年來發展迅速,也有許多關於SDN性能上的研究。不同於傳統的網路架構,SDN主要的概念是將網路程式化,為了使網路管理更為靈活,將交換器中的控制層分離出來。而我們主要關注於OpenFlow 交換器上流量表的大小,目前交換器的流量表是使用Ternary Content Addressable Memory (TCAM),雖然TCAM查找速度快,但也有價格昂貴、功耗大的缺點,這些限制導致流量表的大小受到限制,因此可能發生流量表滿溢的問題,為了解決這個問題,我們會將流量表中的規則利用規則的特徵進行壓縮聚合,進而減少流量表的使用空間。

我們在進行流量聚合前,會根據欄位建立二元樹,每個節點會儲存規則。為了減少流量聚合的時間,會在每個節點建立一種索引,可知道每個規則可壓縮的範圍,以減少流量聚合的時間。為了改進流量聚合的壓縮率,會將流量表的規則依據行為作分類,再由每個分類中規則的數量多寡依序插入二元樹,透過規則的還原與數量大的規則優先進行流量聚合,讓規則的數量減少到最小。並且利用每個規則經過節點時會可知道聚合範圍的索引進行流量聚合,提升流量聚合過程的效率,減少尋找擁有同樣指令規則的時間成本,我們將改良後的方法簡稱為EFAS (Efficient Flow Aggregation Scheme),為更加有效率的流量聚合方法。本篇論文在Linux平台上,使用Floodlight作為控制層中的控制器,並使用Mininet模擬OpenFlow Switch以及網路拓樸環境,實驗中我們使用了mesh、tree和fat tree三種拓樸,透過實驗結果得知,我們提出的索引以及規則分類方法的平均壓縮率較FTRS好約15%,而平均流量聚合時間較FTRS快了約2.0毫秒。
The Software Defined Network(SDN)has been developed rapidly and there are numerous studied on the performance of SDN in recent years. Different from the traditional networks, SDN, which is the programmable networks, has more flexible network management which separate the controller plane away from the network switch. Our thesis focuses on the size of flow table in OpenFlow switch which is implemented by Ternary Content Addressable Memory (TCAM). Although TCAM has the advantage of fast forwarding, it is expensive and power hungry. These shortages limit the size of flow table and may cause the flow table overflow. To solve the problem, we will find the features of flow rules, and aggregate the rules according to the same features to reduce the size usage of flow table.
In this thesis, Flow Table Reduction Scheme (FTRS) is the subject matter we study and improve. Before aggregating the flow rules, we generate the binary tree and build range index on every node to identify the aggregation range, and the index can shorten the execution time of flow aggregation. To improve the compression ratio of flow aggregation, we classify the flow rules by instructions in each classification before inserting into the binary tree, and restore and classify the rules to decrease the number of flow rules to minimum size. The Scheme we proposed named Efficient Flow Aggregation Scheme, is the more efficient flow-aggregation method. With Linux operating system, we use Floodlight as the controller and use Mininet to simulate the OpenFlow Switch and network topology. Furthermore, by using mesh, tree and fat tree topologies in our simulation and it turns out that the average compression ratio of our method is relatively 15% better than that of the FTRS, and the average reduction of 2.0ms of the flow aggregation time.
摘要 i
Abstract ii
內容 iii
表目錄 v
圖目錄 vi
第一章 緒論 1
1.1軟體定義網路(SDN)簡介 1
1.2研究動機和目的 3
1.3 論文架構 3
第二章 相關文獻探討 4
2.1 傳統網路IP路由表的流量聚合演算法 4
2.2 TCAM中封包分類表的流量聚合演算法 4
2.3 OpenFlow 交換器流量表的流量聚合演算法 4
2.4 FTRS研究 5
2.4.1 FTRS的資料結構 6
2.4.2 FTRS 流量聚合演算法 6
第三章 EFAS - IP位址流量聚合方法 8
3.1核心概念 8
3.2 EFAS的說明與舉例 9
3.2.1 規則的分類與排序 11
3.2.2 建立二元樹 15
3.2.3 範圍索引的使用與流量聚合的條件 15
第四章 模擬結果與分析 22
4.1 SDN模擬環境介紹 22
4.1 模擬結果與分析 24
第五章 結論 29
參考文獻 30
[1]D. Kreutz, F. M. V. Ramos, P. E. Veríssimo, C. E. Rothenberg, S. Azodolmolky and S. Uhlig, "Software-Defined Networking: A Comprehensive Survey," in Proceedings of the IEEE, vol. 103, no. 1, pp. 14-76, Jan. 2015.

[2]Andrew R. Curtis, Jeffrey C. Mogul, Jean Tourrilhes, Praveen Yalagandula, Puneet Sharma, and Sujata Banerjee. 2011. DevoFlow: scaling flow management for high-performance networks. SIGCOMM Comput. Commun. Rev. 41, 4 (August 2011), 254-265.

[3]F. Hu, Q. Hao and K. Bao, "A Survey on Software-Defined Network and OpenFlow: From Concept to Implementation," in IEEE Communications Surveys & Tutorials, vol. 16, no. 4, pp. 2181-2206, Fourthquarter 2014.

[4]M G Gouda, X Y Liu, A. Firewall, "design: Consistency completeness and compactness[C]IIDistributed Computing Systems 2004," Proceedings. 24th International Conference on. IEEE, pp. 320-327, 2004.

[5]B. Leng, L. Huang, X. Wang, H. Xu and Y. Zhang, "A mechanism for reducing flow tables in software defined network," 2015 IEEE International Conference on Communications (ICC), London, 2015, pp. 5302-5307.

[6]R. P. Draves, C. King, S. Venkatachary and B. D. Zill, "Constructing optimal IP routing tables," INFOCOM '99. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, New York, NY, 1999, pp. 88-97 vol.1.

[7]Y. Liu, B. Zhang and L. Wang, "FIFA: Fast incremental FIB aggregation," 2013 Proceedings IEEE INFOCOM, Turin, 2013, pp. 1-9.

[8]A. X. Liu, C. R. Meiners and E. Torng, "TCAM Razor: A Systematic Approach Towards Minimizing Packet Classifiers in TCAMs," in IEEE/ACM Transactions on Networking, vol. 18, no. 2, pp. 490-500, April 2010.

[9]C. R. Meiners, A. X. Liu and E. Torng, "Bit weaving: A non-prefix approach to compressing packet classifiers in TCAMs," 2009 17th IEEE International Conference on Network Protocols, Princeton, NJ, 2009, pp. 93-102.

[10]S. Luo, H. Yu and L. M. Li, "Fast incremental flow table aggregation in SDN," 2014 23rd International Conference on Computer Communication and Networks (ICCCN), Shanghai, 2014, pp. 1-8.

[11]TCAMs and OpenFlow – What Every SDN Practitioner Must Know, available: https://www.sdxcentral.com/articles/contributed/sdn-openflow-tcam-need-to-know/2012/07/

[12]Q. Dong, S. Banerjee, J. Wang, D. Agrawal, and A. Shukla, "Packet classifiers in ternary CAMs can be smaller," in Proc. SIGMETRICS, 2006, pp. 311-322.

[13]P. Gupta and N. McKeown, "Algorithms for packet classification," in IEEE Network, vol. 15, no. 2, pp. 24-32, Mar/Apr 2001.

[14]Charles E. Leiserson Fat-trees: universal networks for hardware-efficient supercomputing, IEEE Transactions on Computers, Vol. 34 , no. 10, Oct. 1985, pp. 892-901.

[15]E. W. Dijkstra, "A note on two problems in connexion with graphs," Numerische Mathematik archive,Volume 1 Issue 1, December 1959 Pages 269-271
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