SFabric: a scalable SDN based large layer 2 data center network fabric

被引:0
|
作者
Xiaoyuan Lu
Yanwei Xu
机构
[1] Fudan University,School of Computer Science
[2] Shanghai Engineering Research Center for Broadband Technologies & Applications,undefined
[3] Shanghai B-Star Technology Co.,undefined
[4] Ltd.,undefined
来源
Cluster Computing | 2019年 / 22卷
关键词
Data center; Network fabric; SDN; OpenFlow;
D O I
暂无
中图分类号
学科分类号
摘要
Data centers are now the basis for many Internet and cloud computing services. Trends toward multi-core processors, end-host virtualization, and commodities of scale are pointing to future single-site data centers with millions of virtual end-hosts. The Ethernet/IP style layer 2 and layer 3 network protocols are facing some mixture of inherent limitations in supporting such large topologies: lack of scalability, difficult to management, inflexible in communication, limited support for virtual machine migration. Although several large layer 2 network technologies have been proposed in recent years, they still have several weaknesses that impede them from practical applications such as inflexible, broadcast storms, un-scalability and un-interoperability with existing devices. Software defined networking (SDN) is an emerging promising solution to the above problems due to its outstanding characteristics of control plane and data plane separation, centralized and flexible network management. However, the limited efficiency of the centralized SDN Controller and the large number of routing rules needed in switches are the two faced main challenges in scalability when adopting the existing SDN solutions in large data centers. Therefore, this paper proposes a novel SDN based large layer 2 network fabric for data centers: SFabric, which deals with the two challenges by highly reducing the interactions between the Controller and switches in computing and constructing the paths among switches in advance, and decreasing the number of routing rules in tagging and routing packets at switch levels. A prototype is developed and experimental results prove the good efficiency and scalability of the proposed method.
引用
收藏
页码:6657 / 6668
页数:11
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