胖树数据中心中可变大小虚拟机的高效虚拟网络嵌入

Jun Duan, Yuanyuan Yang
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引用次数: 3

摘要

网络虚拟化是实现云资源共享的技术。虚拟网络嵌入的效率决定了数据中心的费用与收入之比。本文研究了胖树数据中心中的虚拟网络嵌入问题。我们设计了各种方案来嵌入非阻塞多播虚拟网络(NMVNs),这些网络致力于为云用户提供优质的体验。在每个NMVN中,都有从不同大小中选择的虚拟机的自由组合。消除了这些虚拟机之间通信的瓶颈,这样它们就可以始终以其网络接口的全带宽发送数据,即使数据同时发送到多个目的地也是如此。此外,在控制良好的低网络硬件成本的前提下,保证了NMVNs的高性能。我们设计了静态NMVN嵌入(SNE)和动态NMVN嵌入(DNE)两种NMVN嵌入方案。两种方案都支持组播的非阻塞特性。此外,这两种方案各有其独特之处。SNE方案提供了一种无干扰的解决方案,即一个虚拟网络在其生命周期内不知道其他虚拟网络的存在。与SNE相比,DNE方案的硬件成本更低,并且可以根据需要重新配置,为云用户提供更高的灵活性。此外,我们通过理论分析和模拟来验证DNE的开销是最小的,因此大多数云应用程序都可以接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Virtual Network Embedding for Variable Size Virtual Machines in Fat-Tree Data Centers
Network virtualization is the enabling technology for sharing resources on cloud. The efficiency of virtual network embedding determines the expense and revenue ratio of a data center. In this paper, we consider the virtual network embedding problem in fat-tree data centers. We design various schemes to embed Nonblocking Multicast Virtual Networks (NMVNs) which are dedicated to deliver premium experience to cloud users. In each NMVN, there is a free combination of virtual machines selected from variable sizes. The bottleneck of communications between these virtual machines is removed so that they can always send data at full bandwidth of their network interface, even if data is simultaneously sent to multiple destinations. In addition, the high performance of NMVNs is guaranteed at the wellcontrolled low network hardware cost. We design two embedding schemes for NMVNs, named Static NMVN Embedding (SNE) and Dynamic NMVN Embedding (DNE). Both schemes support the nonblocking properties for multicast. Besides, each of the two schemes has its unique features. The SNE scheme provides an interference-free solution, in the sense that a virtual network is not aware of the existence of other virtual networks during its lifetime. The DNE scheme has lower hardware cost than SNE and provides higher flexibility to cloud users by possible reconfigurations when necessary. Additionally, we show through theoretical analysis and simulations to validate that the overhead of DNE is minimal thus acceptable to most cloud applications.
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