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一种源控制的数据中心网络模型。

A source-controlled data center network model.

作者信息

Yu Yang, Liang Mangui, Wang Zhe

机构信息

Institute of Information Science, Beijing Jiaotong University, Beijing, People's Republic of China.

Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, People's Republic of China.

出版信息

PLoS One. 2017 Mar 22;12(3):e0173442. doi: 10.1371/journal.pone.0173442. eCollection 2017.

DOI:10.1371/journal.pone.0173442
PMID:28328925
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5362056/
Abstract

The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN) model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA) as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1) The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2) Vector switches (VS) developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3) The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4) We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS.

摘要

应用软件定义网络(SDN)技术构建数据中心网络已成为一个热门研究课题。SDN架构创新性地将控制平面与数据平面分离,使网络更具软件导向性和灵活性。此外,它提供虚拟多租户、有效的资源调度和集中控制策略,以满足云计算数据中心的需求。然而,网络信息的爆炸式增长给SDN控制器带来了严峻挑战。基于三态内容寻址存储器(TCAM)设备的流存储和查找机制导致了可扩展性受限、成本高和能耗大。鉴于此,本文提出了一种源控制数据中心网络(SCDCN)模型。SCDCN模型应用一种名为向量地址(VA)的新型源路由地址作为分组交换标签。VA完全定义了通信路径,数据转发过程仅依靠VA即可完成。SCDCN架构有四个优点。1)该模型采用分层多控制器,将大规模数据中心网络抽象为一些小的网络域,解决了单个控制器处理能力的限制,降低了计算复杂度。2)核心网络中开发的向量交换机(VS)不再使用TCAM进行表存储和查找,这显著降低了交换机的成本和复杂度。同时,可扩展性问题也能有效解决。3)SCDCN模型简化了新流的建立过程,无需将流表下载到VS。建立新流时消耗的控制信令量可大幅减少。4)我们在NetFPGA平台上设计了VS。统计结果表明,一个VS中的硬件资源消耗约为一个开放流交换机(OFS)的27%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/b1be7749e69a/pone.0173442.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/6ae5c9cd990c/pone.0173442.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/79db9ec89438/pone.0173442.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/0e01068ab994/pone.0173442.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/0ddb16b552c3/pone.0173442.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/c3715444180f/pone.0173442.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/77fbacf64322/pone.0173442.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/1b3a6c426911/pone.0173442.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/b1be7749e69a/pone.0173442.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/6ae5c9cd990c/pone.0173442.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/79db9ec89438/pone.0173442.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/0e01068ab994/pone.0173442.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/0ddb16b552c3/pone.0173442.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/c3715444180f/pone.0173442.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/77fbacf64322/pone.0173442.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/1b3a6c426911/pone.0173442.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1f4/5362056/b1be7749e69a/pone.0173442.g008.jpg

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