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Author Kim, Changhoon ♦ Kandula, Srikanth ♦ Greenberg, Albert ♦ Jain, Navendu ♦ Lahiri, Parantap ♦ Hamilton, James R. ♦ Patel, Parveen ♦ Maltz, David A. ♦ Sengupta, Sudipta
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract To be agile and cost effective, data centers must allow dynamic resource allocation across large server pools. In particular, the data center network should provide a simple flat abstraction: it should be able to take any set of servers anywhere in the data center and give them the illusion that they are plugged into a physically separate, noninterfering Ethernet switch with as many ports as the service needs. To meet this goal, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, performance isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end system--based address resolution to scale to large server pools without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 s---sustaining a rate that is 94% of the maximum possible.
Description Affiliation: Amazon Web Services (Hamilton, James R.) || Microsoft Research (Greenberg, Albert; Jain, Navendu; Kandula, Srikanth; Kim, Changhoon; Lahiri, Parantap; Maltz, David A.; Patel, Parveen; Sengupta, Sudipta)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 54
Issue Number 3
Page Count 10
Starting Page 95
Ending Page 104

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Source: ACM Digital Library