The nature of data center traffic: measurements & analysis
The nature of data center traffic: measurements & analysis
复制标题
DOI：
10.1145/1644893.1644918
复制
发表时间：
2009-11
期刊：
影响因子：
--
通讯作者：
Srikanth Kandula;S. Sengupta;A. Greenberg;Parveen Patel;R. Chaiken
中科院分区：
文献类型：
--
作者：
Srikanth Kandula;S. Sengupta;A. Greenberg;Parveen Patel;R. Chaiken
我们探索数据中心中流量的性质，旨在支持海量数据集的挖掘。我们检测服务器以收集套接字级别的日志，而对性能的影响可以忽略不计。因此，在一个1500台服务器运行的集群中，我们在两个月内积累了大约1PB的测量数据，从中我们获得并报告了流量和拥塞状况和模式的详细视图。我们还考虑是否可以替代地通过从粗粒度计数器数据进行层析推断来获得集群中的业务矩阵。
We explore the nature of traffic in data centers, designed to support the mining of massive data sets. We instrument the servers to collect socket-level logs, with negligible performance impact. In a 1500 server operational cluster, we thus amass roughly a petabyte of measurements over two months, from which we obtain and report detailed views of traffic and congestion conditions and patterns. We further consider whether traffic matrices in the cluster might be obtained instead via tomographic inference from coarser-grained counter data.