ACM Transactions on Computer Systems (TOCS)
A flexible model for resource management in virtual private networks
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Principles and Practices of Interconnection Networks
Principles and Practices of Interconnection Networks
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Towards a next generation data center architecture: scalability and commoditization
Proceedings of the ACM workshop on Programmable routers for extensible services of tomorrow
Floodless in seattle: a scalable ethernet architecture for large enterprises
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
A scalable, commodity data center network architecture
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Dcell: a scalable and fault-tolerant network structure for data centers
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
VL2: a scalable and flexible data center network
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
BCube: a high performance, server-centric network architecture for modular data centers
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
The nature of data center traffic: measurements & analysis
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Symbiotic routing in future data centers
Proceedings of the ACM SIGCOMM 2010 conference
SPAIN: COTS data-center Ethernet for multipathing over arbitrary topologies
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
Load balanced Birkhoff-von Neumann switches, part I: one-stage buffering
Computer Communications
Windows Azure Storage: a highly available cloud storage service with strong consistency
SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
Resource efficient computing for warehouse-scale datacenters
Proceedings of the Conference on Design, Automation and Test in Europe
Scalable multi-access flash store for big data analytics
Proceedings of the 2014 ACM/SIGDA international symposium on Field-programmable gate arrays
Review: A survey on architectures and energy efficiency in Data Center Networks
Computer Communications
| Hi-index | 48.22 |
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.