Scalable and Cost-Effective Interconnection of Data-Center Servers Using Dual Server Ports

Scalable and Cost-Effective Interconnection of Data-Center Servers Using Dual Server Ports
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DOI:
10.1109/tnet.2010.2053718
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发表时间:
2011-02
期刊:
IEEE/ACM Transactions on Networking
影响因子:
--
通讯作者:
Dan Li;Chuanxiong Guo;Haitao Wu;Kun Tan;Yongguang Zhang;Songwu Lu;Jianping Wu
Dan Li;Chuanxiong Guo;Haitao Wu;Kun Tan;Yongguang Zhang;Songwu Lu;Jianping Wu
中科院分区:
其他
文献类型:
--
作者:
Dan Li;Chuanxiong Guo;Haitao Wu;Kun Tan;Yongguang Zhang;Songwu Lu;Jianping Wu

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数据中心网络的目标是以低设备成本互连大量服务器机器,同时提供高网络容量和高对分宽度。众所周知,当前通过网络交换机的树形层次结构连接服务器的做法无法满足这些要求。在本文中,我们探索了一种新的服务器互连结构。我们观察到,当今数据中心使用的商用服务器通常配有两个内置以太网端口,一个用于网络连接,另一个用于备份目的。我们相信,如果两个端口都积极用于网络连接,我们就可以构建一个可扩展、经济高效的互连结构,而无需昂贵的高级大型交换机或服务器上的任何额外硬件。我们设计了这样一个网络结构,称为FiConn。虽然该结构中服务器节点度仅为 2,但我们已经证明 FiConn 具有高度可扩展性,可以容纳数十万台低直径和高二分宽度的服务器。我们开发了一种低开销的流量感知路由机制,以根据动态流量状态提高有效链路利用率。我们还提出了如何增量部署 FiConn。
The goal of data-center networking is to interconnect a large number of server machines with low equipment cost while providing high network capacity and high bisection width. It is well understood that the current practice where servers are connected by a tree hierarchy of network switches cannot meet these requirements. In this paper, we explore a new server-interconnection structure. We observe that the commodity server machines used in today's data centers usually come with two built-in Ethernet ports, one for network connection and the other left for backup purposes. We believe that if both ports are actively used in network connections, we can build a scalable, cost-effective interconnection structure without either the expensive higher-level large switches or any additional hardware on servers. We design such a networking structure called FiConn. Although the server node degree is only 2 in this structure, we have proven that FiConn is highly scalable to encompass hundreds of thousands of servers with low diameter and high bisection width. We have developed a low-overhead traffic-aware routing mechanism to improve effective link utilization based on dynamic traffic state. We have also proposed how to incrementally deploy FiConn.