As data centers become more and more central in Internet
\ncommunications, both research and operations communities
\nhave begun to explore how to better design and manage
\nthem. In this paper, we present a preliminary empirical
\nstudy of end-to-end traffic patterns in data center networks
\nthat can inform and help evaluate research and operational
\napproaches. We analyze SNMP logs collected at 19 data cen-
\nters to examine temporal and spatial variations in link loads
\nand losses. We find that while links in the core are heavily
\nutilized the ones closer to the edge observe a greater degree
\nof loss. We then study packet traces collected at a small
\nnumber of switches in one data center and find evidence of
\nON-OFF traffic behavior. Finally, we develop a framework
\nthat derives ON-OFF traffic parameters for data center traf-
\nfic sources that best explain the SNMP data collected for the
\ndata center. We show that the framework can be used to
\nevaluate data center traffic engineering approaches. We are
\nalso applying the framework to design network-level traffic
\ngenerators for data centers.<\/p>\n","protected":false},"excerpt":{"rendered":"
As data centers become more and more central in Internet communications, both research and operations communities have begun to explore how to better design and manage them. In this paper, we present a preliminary empirical study of end-to-end traffic patterns in data center networks that can inform and help evaluate research and operational approaches. We […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"Association for Computing Machinery, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"ACM SIGCOMM Workshop: Research on Enterprise Networking ","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Copyright \u00a9 2007 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and\/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. 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