数据流特征感知的交换机流表智能更新方法

doi:10.11772/j.issn.1001-9081.2016.07.1772

计算机应用 ›› 2016, Vol. 36 ›› Issue (7): 1772-1778.DOI: 10.11772/j.issn.1001-9081.2016.07.1772

数据流特征感知的交换机流表智能更新方法

姜立立^1,2, 曾国荪¹, 丁春玲³

1. 同济大学计算机科学及技术系, 上海 200092;
2. 高效能服务器和存储技术国家重点实验室(浪潮集团有限公司), 济南 250101;
3. 同济大学化学系, 上海 200092

收稿日期:2016-01-25 修回日期:2016-03-06 出版日期:2016-07-10 发布日期:2016-07-14
通讯作者: 姜立立
作者简介:姜立立(1992-),女,浙江温州人,硕士研究生,主要研究方向:软件定义网络、流表更新策略;曾国荪(1964-),男,江西吉安人,教授,博士生导师,博士,CCF会员,主要研究方向:并行计算、可信软件、信息安全;丁春玲(1965-),女,江西宜春人,高级工程师,硕士,主要研究方向:建模分析。
基金资助:
国家自然科学基金资助项目（61272107）；上海市优秀学科带头人计划项目（10XD1404400）；华为创新研究计划项目（IRP-2013-12-03）；高效能服务器和存储技术国家重点实验室开放基金资助项目（2014HSSA10）。

Intelligent update method for flow table in switch through analyzing data flow characteristics

JIANG Lili^1,2, ZENG Guosun¹, DING Chunling³

1. Department of Computer Science and Technology, Tongji University, Shanghai 200092, China;
2. State Key Laboratory of High-end Server & Storage Technology (INSPUR Company Limited), Jinan Shandong 250101, China;
3. Department of Chemistry, Tongji University, Shanghai 200092, China

Received:2016-01-25 Revised:2016-03-06 Online:2016-07-10 Published:2016-07-14
Supported by:
This work is partially supported by the National Natural Foundation Program of China (61272107), the Program of Shanghai Subject Chief Scientist (10XD1404400), Huawei Innovation Research Project (IRP-2013-12-03), the Open Foundation of the State Key Laboratory of High-end Server & Storage Technology (2014HSSA10).

摘要/Abstract

摘要： 针对软件定义网络（SDN）中交换机流表匹配率低的问题，提出了数据流特征感知的交换机流表智能更新方法。首先，论述流表项的生存超时时间timeout对数据包匹配的影响，并且分析比较基于先进先出（FIFO）、近期最少使用（LRU）等一般方法存在的不足；其次，根据流表项的生存时间和数据流的特征密切相关的思想，利用基于隐马尔可夫模型（HMM）的深度流检测（DFI）技术对数据流进行分类；最后，根据流表资源和控制器计算资源状况，实现对不同类型数据流流表项的智能更新。采用校园数据中心网络行为数据的模拟实验表明，与流表更新的一般方法相比，智能方法能使流表匹配率提高5%以上，对SDN交换机的管理有实际意义。

关键词: 软件定义网络, 交换机, 传输数据流, 流表更新方法, 匹配率

Abstract: To address the low matching rate of flow table, an intelligent update method for flow table in Software Defined Network (SDN) switch was proposed. First, the impact of timeout value on the packet matching was described, besides, the shortcomings of First In First Out (FIFO), Least Recently Used (LRU) and other common methods were analyzed and compared. Secondly, based on the reality of survival time of the flow entry related closely to the characteristics of data flow, the Hidden Markov Model (HMM)-based Deep Flow Inspection (DFI) technology was used to classify the data flow. Finally, according to the condition of the flow table resources and controller's computing resources, the intelligent update of the flow entry of different type of data flow was realized. The simulation experiments conducted on data center behavior data of real campus indicate that the proposed method can improve more than 5% of the matching rate compared with the common methods, and it has a practical significance to the management of the SDN switch.

Key words: Software Defined Network (SDN), switch, transport data flow, flow table update method, matching rate

中图分类号:

TP393.07

姜立立, 曾国荪, 丁春玲. 数据流特征感知的交换机流表智能更新方法[J]. 计算机应用, 2016, 36(7): 1772-1778.

JIANG Lili, ZENG Guosun, DING Chunling. Intelligent update method for flow table in switch through analyzing data flow characteristics[J]. Journal of Computer Applications, 2016, 36(7): 1772-1778.

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数据流特征感知的交换机流表智能更新方法

Intelligent update method for flow table in switch through analyzing data flow characteristics

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