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应用于协议无感知转发交换机的流缓存方法

曹作伟 陈晓 倪宏 叶晓舟

曹作伟, 陈晓, 倪宏, 叶晓舟. 应用于协议无感知转发交换机的流缓存方法[J]. 电子与信息学报, 2018, 40(11): 2772-2778. doi: 10.11999/JEIT180042
引用本文: 曹作伟, 陈晓, 倪宏, 叶晓舟. 应用于协议无感知转发交换机的流缓存方法[J]. 电子与信息学报, 2018, 40(11): 2772-2778. doi: 10.11999/JEIT180042
Zuowei CAO, Xiao CHEN, Hong NI, Xiaozhou YE. Flow Caching in Protocol Oblivious Forwarding Switches[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2772-2778. doi: 10.11999/JEIT180042
Citation: Zuowei CAO, Xiao CHEN, Hong NI, Xiaozhou YE. Flow Caching in Protocol Oblivious Forwarding Switches[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2772-2778. doi: 10.11999/JEIT180042

应用于协议无感知转发交换机的流缓存方法

doi: 10.11999/JEIT180042
基金项目: 国家科技重大专项项目(2017ZX03001019)
详细信息
    作者简介:

    曹作伟:男,1991年生,博士生,研究方向为协议无感知转发、可编程数据平面等

    陈晓:男,1964年生,研究员,研究方向为网络通信、新媒体技术等

    倪宏:男,1964年生,研究员,研究方向为网络通信、新媒体技术等

    叶晓舟:男,1980年生,研究员,研究方向为嵌入式多核网络处理器、新媒体技术等

    通讯作者:

    陈晓  xxchen@dsp.ac.cn

  • 中图分类号: TP393

Flow Caching in Protocol Oblivious Forwarding Switches

Funds: The National Science and Technology of Major Projects of China (2017ZX03001019)
  • 摘要: 协议无感知转发支持任意协议的解析和处理,增强了软件定义网络的可编程能力。为提高转发性能,该文提出一种应用于协议无感知转发交换机的流缓存方法,通过识别匹配和动作的依赖关系,得到匹配字段的绝对位置,用以预先解析报文。为确保流缓存的加速效果,根据匹配类型与表项数量选择应用流缓存的流表。此外,该文对比了单流表缓存与多流表缓存对转发性能的提升,并提出了根据网络流量实际情况的自适应切换策略。通过扩展POFSwitch实现所提方法,并用实际规则与骨干网流量进行验证,应用流缓存后,交换机报文转发速率提升了220%。流缓存可以为可编程数据平面提供更高的转发性能。
  • 图  1  POF流表的报文处理流程

    图  2  匹配字段与动作间的依赖关系

    图  3  POF流缓存数据路径

    图  4  应用流缓存的流表

    图  5  环境拓扑

    图  6  流表配置

    图  7  应用流缓存前后的报文转发速率对比

    图  8  多流表缓存与单流表缓存的转发速率与命中率对比

    表  1  依赖关系识别算法

     算法1 依赖关系识别算法 $\operatorname{Dep} (e,F)$
     (1) for each action $a$ in entry $e$ in reverse order
     (2)  if $a\cdot g(F) \ne \varnothing$
     (3)    $\quad F = a\cdot g(F)$
     (4)    $\quad F = F + \{ {\rm{input \; fields \; of }}\; a\} $
     (5) return $F$
    下载: 导出CSV

    表  2  几种典型的匹配算法

    匹配类型 LM EM LPM MM
    匹配算法 线性 哈希 PartitionSort 类S-Trie
    $f\left( n \right)$ $O\left( 1 \right)$ $O\left( 1 \right)$ $O\left( {p \cdot \left( {d + \lg n} \right)} \right)$ $O\left( {d \cdot \lg n} \right)$
    下载: 导出CSV

    表  3  流表选择算法

     算法2 流表选择算法 $\operatorname{Select} (X)$
     (1) label flow table $X$ as discovered
     (2) delete type (3) actions and merge duplicate entries
     (3) if $X$ is LPM or MM
     (4) if entry number of $X$ ${\rm{ > Thr}}$
     (5) label $X$ as worth caching
     (6) for each entry $e$ in $X$
     (7) let $Y\;$ as the table which $e$ leads
     (8) if $Y\;$ is not discovered
     (9) let $F'(Y\;) = {Φ} $
     (10) recursively call $\operatorname{Select} (Y\;)$
     (11) if $X$ is worth caching and $Y\;$ is worth caching
     (12) $F'(Y\;) = F'(Y\;) + \operatorname{Dep} (e,F(Y\;))$
     (13) if $X$ is worth caching
     (14) let $F(X) = $match fields of $X$
     (15) for each child table $Y\;$ worth caching
     (16) $F(X) = F(X) + F'(Y\;)$
    下载: 导出CSV
  • MCKEOWN N, ANDERSON T, BALAKRISHNAN H, et al. OpenFlow: Enabling innovation in campus networks[J]. ACM SIGCOMM Computer Communication Review, 2008, 38(2): 69–74 doi: 10.1145/1355734.1355746
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出版历程
  • 收稿日期:  2018-01-11
  • 修回日期:  2018-06-14
  • 网络出版日期:  2018-06-30
  • 刊出日期:  2018-11-01

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