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Data plane verification (DPV) is important for finding network errors.Current DPV tools employ a centralized architecture, where a server collectsthe data planes of all devices and verifies them. Despite substantial effortson accelerating DPV, this centralized architecture is inherently unscalable. Inthis paper, to tackle the scalability challenge of DPV, we circumvent thescalability bottleneck of centralized design and design Coral, a distributed,on-device DPV framework. The key insight of Coral is that DPV can betransformed into a counting problem on a directed acyclic graph, which can benaturally decomposed into lightweight tasks executed at network devices,enabling scalability. Coral consists of (1) a declarative requirementspecification language, (2) a planner that employs a novel data structure DVNetto systematically decompose global verification into on-device counting tasks,and (3) a distributed verification (DV) protocol that specifies how on-deviceverifiers communicate task results efficiently to collaboratively verify therequirements. We implement a prototype of Coral. Extensive experiments withreal-world datasets (WAN/LAN/DC) show that Coral consistently achieves scalableDPV under various networks and DPV scenarios, i.e., up to 1250 times speed upin the scenario of burst update, and up to 202 times speed up on 80% quantileof incremental verification, than state-of-the-art DPV tools, with littleoverhead on commodity network devices.

Switch as a Verifier: Toward Scalable Data Plane Checking via Distributed, On-Device Verification