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Exploiting locality in distributed SDN control

Open access
Schmid, Stefan, Suomela, Jukka·2013·Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking

Abstract

Large SDN networks will be partitioned in multiple controller domains; each controller is responsible for one domain, and the controllers of adjacent domains may need to communicate to enforce global policies. This paper studies the implications of the local network view of the controllers. In particular, we establish a connection to the field of local algorithms and distributed computing, and discuss lessons for the design of a distributed control plane. We show that existing local algorithms can be used to develop efficient coordination protocols in which each controller only needs to respond to events that take place in its local neighborhood. However, while existing algorithms can be used, SDN networks also suggest a new approach to the study of locality in distributed computing. We introduce the so-called supported locality model of distributed computing. The new model is more expressive than the classical models that are commonly used in the design and analysis of distributed algorithms, and it is a better match with the features of SDN networks.

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Metadata

Authors
Schmid, S., & Suomela, J.
Venue
Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking
Publisher
ACM
Published
2013-08-16
Pages
121-126
OpenAlex
W2110738524
Cited by
200
References
0
FWCI
19.24
Type
conference paper
Language
en
Open access
gold

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CoChat. (2026). Citation check: Exploiting locality in distributed SDN control. https://app.cochat.ai/papers/10.1145/2491185.2491198
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Schmid, S., & Suomela, J. (2013). Exploiting locality in distributed SDN control. Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking. https://doi.org/10.1145/2491185.2491198

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.