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arXiv 0907.4810cs.DC
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The Open Cloud Testbed:利用高性能网络服务的云计算广域试验床

The Open Cloud Testbed: A Wide Area Testbed for Cloud Computing Utilizing High Performance Network Services

Robert Grossman, Yunhong Gu, Michal Sabala, Collin Bennet, Jonathan Seidman, Joe Mambratti

摘要:

最近,已经开发了许多用于数据密集型计算的云平台和服务,包括Hadoop,Sector,CloudStore(以前的KFS),HBase和Thrift。为了对这些系统的性能进行基准测试,研究它们的互操作性,并基于灵活的计算节点和网络配置功能试验新服务,我们设计并实现了一个名为开放云测试床(OCT)的大规模测试床。目前,OCT在四个数据中心拥有120个节点:巴尔的摩、芝加哥(两个地点)和圣地亚哥。与其他云测试平台相比,这些云测试平台位于较小的地理区域,并且基于商品互联网服务,OCT是一个广域测试平台,四个数据中心与基于专用光路基础的高性能10 Gb/s网络连接。该测试平台可以满足对其他类型的分布式基础设施提出挑战的超大数据流的要求。我们还开发了几个实用程序来支持云计算系统和服务的开发,包括新型节点和网络供应服务、监控系统和RPC系统。在本文中,我们描述了OCT的架构和监控系统。我们还描述了一些基准,我们开发和一些互操作性的研究,我们使用这些基准进行。

英文摘要:

Recently, a number of cloud platforms and services have been developed for data intensive computing, including Hadoop, Sector, CloudStore (formerly KFS), HBase, and Thrift. In order to benchmark the performance of these systems, to investigate their interoperability, and to experiment with new services based on flexible compute node and network provisioning capabilities, we have designed and implemented a large scale testbed called the Open Cloud Testbed (OCT). Currently the OCT has 120 nodes in four data centers: Baltimore, Chicago (two locations), and San Diego. In contrast to other cloud testbeds, which are in small geographic areas and which are based on commodity Internet services, the OCT is a wide area testbed and the four data centers are connected with a high performance 10Gb/s network, based on a foundation of dedicated lightpaths. This testbed can address the requirements of extremely large data streams that challenge other types of distributed infrastructure. We have also developed several utilities to support the development of cloud computing systems and services, including novel node and network provisioning services, a monitoring system, and a RPC system. In this paper, we describe the OCT architecture and monitoring system. We also describe some benchmarks that we developed and some interoperability studies we performed using these benchmarks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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