S-fabric: towards scalable and incremental SDN deployment in data centers

2017 | conference paper. A publication with affiliation to the University of Göttingen.

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​S-fabric: towards scalable and incremental SDN deployment in data centers​
Shen, H. ; Wang, H. ; Wieder, P.   & Yahyapour, R. ​ (2017)
​Proceedings of the 2017 International Conference on Telecommunications and Communication Engineering pp. 25​-29. ​ICTCE '17​, Osaka, Japan.
New York, USA​: Association for Computing Machinery. DOI: https://doi.org/10.1145/3145777.3145790 

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Authors
Shen, Haoyun ; Wang, Hao ; Wieder, Philipp ; Yahyapour, Ramin 
Abstract
Scalable and robust SDN requires the controller to be distributed. In many SDN designs, the distributed controllers are acting as replicas by forming clusters. For large-scale data centers across multiple geographically distributed locations, the controllers have to maintain a synchronized global view. These restrict themselves on single point of failure, low scalability, more communication effort, bad isolation, and rigid deployment. In this paper, we propose S-Fabric, a novel data center network design, which provides a sliced control plane and a policy-based user-defined data plane. By slicing the network through flows, and assigning a non-replica controller to each slice, S-Fabric achieves flexibility and elasticity, while ensuring isolation and separation. We leverage (but not limited to) a two-tiered spine and leaf architecture, and define forwarding rules for spine, leaf and edge switch respectively. By simplifying the flow table, S-Fabric keeps the number of forwarding rules on spine switches equal to the number of used leaf/edge ports inside a data center. By matching subnets in slices to VLANs on the edge switches, S-Fabric brings backwards compatibility to traditional data centers. S-Fabric enables an incremental deployment of SDN in traditional data centers, since it requires no SDN capability on the spine/core switches.
Issue Date
2017
Publisher
Association for Computing Machinery
Organization
Gesellschaft für wissenschaftliche Datenverarbeitung 
Conference
ICTCE '17
ISBN
978-1-4503-5315-1
Conference Place
Osaka, Japan
Event start
2017-10-22
Event end
2017-10-24
Language
English

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