Study on Big Data Center Traffic Management Based on the Separation of Large-Scale Data Stream

Hyoungwoo Park, I. Yeo, Jongsuk Lee, H. Jang
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引用次数: 26

Abstract

The network of traditional data center has been usually designed and constructed for the provision of user's equal access of data centre's resource or data. Therefore, network administrators have a strong tendency to manage user traffic from the viewpoint that the traffic has a similar size and characteristics. But, the emersion of big data begins to make data centers have to deal with 1015 byte-data transfer at once. Such a big data transfer can cause problems in network traffic management in the existed data center. And, the tiered network architecture of the legacy data center magnifies the magnitude of the problems. One of the well-known big data in science is from large hadron collider such as LHC in Swiss CERN. CERN LHC generates multi-peta byte data per year. From our experience of CERN data service, this paper showed the impact of network traffic affected by large-scale data stream using NS2 simulation, and then, suggested the evolution direction based on separating of large-scale data stream for the big data center's network architecture.
基于大规模数据流分离的大数据中心流量管理研究
传统数据中心的网络通常是为了保证用户对数据中心资源或数据的平等访问而设计和构建的。因此,网络管理员有一种强烈的倾向,从流量大小和特征相似的角度来管理用户流量。但是,大数据的出现开始使数据中心不得不一次处理1015字节的数据传输。这样的大数据传输会给现有数据中心的网络流量管理带来问题。而且,传统数据中心的分层网络体系结构放大了问题的严重性。科学上著名的大数据之一是来自瑞士欧洲核子研究中心的大型强子对撞机(LHC)。欧洲核子研究中心大型强子对撞机每年产生多个字节的数据。本文从CERN数据服务的经验出发,利用NS2模拟展示了大规模数据流对网络流量的影响,并在此基础上提出了基于大规模数据流分离的大数据中心网络架构的演进方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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