DiG:网格中的数据中心

Hardik Soni, D. Saucez, T. Turletti
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引用次数: 4

摘要

我们见证了大量与数据中心和云基础设施相关的研究工作,但评估往往仅限于小规模的场景,因为很少有研究人员能够接触到真实的基础设施,将他们的想法与现实进行对比。在本演示中,我们将展示我们的实验自动化工具DiG(网格中的数据中心),它显式地在网格中分配物理资源以模拟数据中心和云网络。DiG允许人们利用网格基础设施来评估与大规模数据中心和云环境相关的研究想法,并具有真实的流量工作负载。根据实验中链路和主机的需求,在尊重网格中可用物理资源的情况下,实现了目标网络拓扑构建过程的自动化。我们将展示DiG如何自动构建一个由数百台执行各种Hadoop密集型工作负载的服务器组成的大型数据中心拓扑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DiG: Data-centers in the Grid
We are witnessing a considerable amount of research work related to data center and cloud infrastructures but evaluations are often limited to small-scale scenarios as very few researchers have access to a real infrastructure to confront their ideas to reality. In this demo we will reveal our experiment automation tool, DiG (Data centers in the Grid), which explicitly allocates physical resources in grids to emulate data center and cloud networks. DiG allows one to utilize grid infrastructures to evaluate research ideas pertaining to data centers and cloud environments at massive scale and with real traffic workload. We have automated the procedure of building target network topologies while respecting available physical resources in the grid against the demand of links and hosts in the experiment. We will present a showcase where DiG automatically builds a large data center topology composed of hundreds of servers executing various Hadoop intensive workloads.
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