Software defined data center network with hybrid routing

Yue-ping CAI; Chang-ping WANG

doi:10.11959/j.issn.1000-436x.2016071

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Software defined data center network with hybrid routing

academic paper | 更新时间：2024-06-05

- Software defined data center network with hybrid routing
- Journal of Communications Vol. 37, Issue 4, Pages: 44-52(2016)
- 作者机构：
  
  重庆大学通信工程学院，重庆400030
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61301119);Research Fund of Young Scholars for the Doctoral Program of Higher Education of Ministry of Education(20120191120025);Scientific Research Foundation for the Returned Overseas Chinese Scholars of Ministry of Education(1020607820140002)
- DOI：10.11959/j.issn.1000-436x.2016071
  CLC： TP393
- Online First：2016-04，
  
  Published：25 April 2016
- 稿件说明：
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Yue-ping CAI, Chang-ping WANG. Software defined data center network with hybrid routing[J]. Journal of Communications, 2016, 37(4): 44-52.
DOI：

Yue-ping CAI, Chang-ping WANG. Software defined data center network with hybrid routing[J]. Journal of Communications, 2016, 37(4): 44-52. DOI： 10.11959/j.issn.1000-436x.2016071.

摘要

针对数据中心网络流量大小分布不均匀、传输性能需求不相同的特征，提出了面向传统树型数据中心网络结构的软件定义混合路由机制SHR（software-defined hybrid routing）。SHR通过统计计算将数据流分为大流和小流，为满足其不同的传输性能需求，对大流采用自适应路由算法，对小流采用流量无视路由算法。SHR 在OpenFlow机制的基础上，将部分控制权从控制器下放至交换机，以减轻网络的额外负载。在Fat-Tree网络拓扑结构上建立流量模型进行性能分析与仿真实验，结果表明，与传统的等价多路径转发 ECMP 算法相比，SHR 能够提高网络吞吐量，降低数据流丢弃率和分组端到端时延，同时减轻网络的额外负载。

Abstract

In the current data center networks

the flow size distribution is not uniform and the transmission performance requirements of elephant flows and mice flows are different. To address this issue

a software-defined hybrid routing (SHR) scheme was proposed. SHR differentiate data flows by statistical calculat nt flows utilize the adap-tive routing algorithm while the mice flows use the oblivious routing algorithm. SHR extends the OpenFlow scheme by offloading some basic functions such as flow statistical detection and mice flow forwarding to switches to reduce the switch-controller interaction overhead. Performance evaluations of SHR were carried out using the fat-tree network to-pology. Results show that SHR can effectively increase network throughput and reduce the flow dropping rate as well as packet delay compared with the traditional ECMP algorithm.

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references

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