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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Journal ArticleDOI
Capacity-Aware Topology Resilience in Software-Defined Networks
Usman Ashraf,Chau Yuen +1 more
TL;DR: This work proposes a proactive network-topology resilience scheme against worst case adversarial multiswitch failures by installing backup switches at key locations to maximize long-term traffic demands and develops mixed integer linear programming formulations to maximize aggregate demand satisfaction and maximize the minimum fair demand satisfaction.
Proceedings ArticleDOI
Design of SDN-Enabled Cloud Data Center
TL;DR: A novel design of an SDN-enabled cloud data center which addresses important traffic engineering issues, that includes auto topology discovery, auto addressing, auto routing, load balancing, and fast fault detection and recovery is presented.
Proceedings ArticleDOI
wFlatnet: Introducing Wireless in Flatnet Data Center Network
TL;DR: Wang et al. as mentioned in this paper proposed a new network architecture, called wFlatnet, which adds wireless links to the network as shortcuts aiming at minimizing the path length without adding a burden of installation and cost.
Journal ArticleDOI
Online-Batch Joint Routing and Channel Allocation for Hybrid Data Center Networks
TL;DR: This paper investigates the issue of jointly: 1) routing and 2) channel allocating, in both online and batch arrival modes in HDCN, and proposes a new strategy named joint routing and channel allocation algorithm that makes use of the Blossom algorithm and sequentially computes the optimal routing communication paths.
Proceedings ArticleDOI
Exploiting in-network processing for big data management
TL;DR: In-network processing is proposed as a way of achieving network-awareness to decrease bandwidth usage by custom routing, redundancy elimination, and on-path data reduction, and can significantly improve query throughput in a DDPS by performing partial data reduction within the network.
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