Flash: Fast, consistent data plane verification for large-scale network settings

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Abstract

Data plane verification can be an important technique to reduce network disruptions, and researchers have recently made significant progress in achieving fast data plane verification. However, as we apply existing data plane verification techniques to large-scale networks, two problems appear due to extremes. First, existing techniques cannot handle too-fast arrivals, which we call update storms, when a large number of data plane updates must be processed in a short time. Second, existing techniques cannot handle well too-slow arrivals, which we call long-Tail update arrivals, when the updates from a number of switches take a long time to arrive. This paper presents Flash, a novel system that achieves fast, consistent data plane verification when update arrivals can include update storms, long-Tail update arrivals, or both. In particular, Flash introduces a novel technique called fast inverse model transformation to swiftly transform a large block of rule updates to a block of conflict-free updates to efficiently handle update storms. Flash also introduces consistent, efficient, early detection, a systematic mechanism and associated novel algorithms to detect data plane violations with incomplete information, to avoid being delayed by long-Tail arrivals. We fully implement Flash and conduct extensive evaluations under various settings. Using the data plane of a large-scale network, we show that compared with state-of-The-Art sequential per-update verification systems, Flash is 9,000x faster.

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APA

Guo, D., Chen, S., Gao, K., Xiang, Q., Zhang, Y., & Yang, Y. R. (2022). Flash: Fast, consistent data plane verification for large-scale network settings. In SIGCOMM 2022 - Proceedings of the ACM SIGCOMM 2022 Conference (pp. 314–335). Association for Computing Machinery, Inc. https://doi.org/10.1145/3544216.3544246

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