Journal ArticleDOI
VL2: a scalable and flexible data center network
Albert Greenberg,James R. Hamilton,Navendu Jain,Srikanth Kandula,Changhoon Kim,Parantap Lahiri,David A. Maltz,Parveen Patel,Sudipta Sengupta +8 more
TLDR
VL2 is 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 and can be deployed today, and a working prototype is built.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.read more
Citations
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Proceedings ArticleDOI
Skipping congestion-links for coflow scheduling
TL;DR: This paper designs and implements SkipL, a congestion-aware coflow scheduler which could detect congestion and schedules coflows at end-hosts to effectively reduce coflow completion time and reduces the average Coflow Completion Time compared to the per-flow fair sharing scheduling method and Varys.
Proceedings ArticleDOI
Understanding Multi-Path Routing Algorithms in Datacenter Networks
Zhenzao Wen,Linghe Kong,Guihai Chen,Muhammad Khurram Khan,Shahid Mumtaz,Joel J. P. C. Rodrigues +5 more
TL;DR: A customized simulator DRE is developed based on OMNET++ simulation environment and INET framework, and 5 state-of-the-art multi-path routing algorithms in datacenter covering various topologies and metrics are measured, which can promote future multi- path routing algorithm designs.
Proceedings ArticleDOI
HOLMES : Holistic Mice-Elephants Stochastic Scheduling in Data Center Networks
TL;DR: A novel flow control scheme, HOLMES (HOListic Mice-Elephants Stochastic), which offers a holistic view of global congestion awareness as a stochastic scheduler of mixed mice-elephants data flows in Data Center Networks (DCNs).
Dissertation
Understanding and Improving the Efficiency of Failure Resilience for Big Data Frameworks
TL;DR: The design, implementation and evaluation of RCMP, a MapReduce system originating from the fundamental insight that using data replication to enable failure resilience oftentimes leads to significant and unnecessary increases in computation running time is presented.
Proceedings ArticleDOI
Patching up Network Data Leaks with Sweeper
TL;DR: Sweeper is introduced, a hardware extension and API that allows applications to mark consumed network buffers so that hardware then skips writing marked buffers back to memory, drastically reducing memory bandwidth consumption and mitigating the performance penalty of network data leaks.
References
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