DOCSDN: Dynamic and Optimal Configuration of Software-Defined Networks

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Abstract

Networks are designed with functionality, security, performance, and cost in mind. Tools exist to check or optimize individual properties of a network. These properties may conflict, so it is not always possible to run these tools in series to find a configuration that meets all requirements. This leads to network administrators manually searching for a configuration. This need not be the case. In this paper, we introduce a layered framework for optimizing network configuration for functional and security requirements. Our framework is able to output configurations that meet reachability, bandwidth, and risk requirements. Each layer of our framework optimizes over a single property. A lower layer can constrain the search problem of a higher layer allowing the framework to converge on a joint solution. Our approach has the most promise for software-defined networks which can easily reconfigure their logical configuration. Our approach is validated with experiments over the fat tree topology, which is commonly used in data center networks. Search terminates in between 1–5 min in experiments. Thus, our solution can propose new configurations for short term events such as defending against a focused network attack.

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APA

Curry, T., Callahan, D., Fuller, B., & Michel, L. (2019). DOCSDN: Dynamic and Optimal Configuration of Software-Defined Networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11547 LNCS, pp. 456–474). Springer Verlag. https://doi.org/10.1007/978-3-030-21548-4_25

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