DCNSim: a unified and cross-layer computer architecture simulation framework for data center network research

Nongda Hu, Long Li, Binzhang Fu, Tao Li, Xiufeng Sui, Lixin Zhang
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引用次数: 2

Abstract

Within today's large-scale data centers, the inter-node communication is often the major bottleneck. This fact recently blooms the data center network (DCN) research. Since building a real data center is cost prohibitive, most of DCN studies rely on simulations. Unfortunately, state-of-the-art network simulators have limited support for real world applications, which prevents researchers from first-hand investigation. To address this issue, we developed a unified and cross-layer simulation framework, namely the DCNSim. By leveraging the two widely deployed simulators, DCNSim introduces computer architecture solutions into DCN research. With DCNSim, one could run packet-level network simulation driven by commercial applications while varying computer and network parameters, such as CPU frequency, memory access latency, network topology and protocols. With extensive validations, we show that DCNSim could accurately capture performance trends caused by changing computer and network parameters. Finally, we argue that future DCN researches should consider computer architecture factors via several case studies.
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DCNSim:用于数据中心网络研究的统一的跨层计算机体系结构仿真框架
在当今的大型数据中心中,节点间通信通常是主要的瓶颈。这一事实最近掀起了数据中心网络(DCN)的研究热潮。由于构建真实的数据中心成本过高,大多数DCN研究都依赖于模拟。不幸的是,最先进的网络模拟器对现实世界应用的支持有限,这阻碍了研究人员的第一手调查。为了解决这个问题,我们开发了一个统一的跨层仿真框架,即DCNSim。通过利用这两个广泛部署的模拟器,DCNSim将计算机体系结构解决方案引入DCN研究。使用DCNSim,可以在改变计算机和网络参数(如CPU频率、内存访问延迟、网络拓扑和协议)的情况下运行由商业应用程序驱动的数据包级网络模拟。通过大量的验证,我们表明DCNSim可以准确地捕获由计算机和网络参数变化引起的性能趋势。最后,我们认为未来的DCN研究应该考虑计算机体系结构因素。
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