A critical problem with the consensus protocols underlying blockchains is that they do not scale well. As the number of participants trying to achieve consensus increases, increasing network traffic from topology-oblivious broadcasts can quickly overwhelm the network, or, when using centralized consensus protocols, overwhelm the central coordinator. Thus, achieving strong consensus is typically restricted to a handful of participants, or systems must resort to weaker forms of consensus, such as those using proof of work. To address this problem, we propose Canopus, a highly-parallel consensus protocol that exploits modern data center network topology, parallelism, and consensus semantics to achieve scalability. Our key insight is to make network communication patterns topology-aware. In our prototype implementation, Canopus achieves rates as high as 5m linearizable transactions/second over 27 nodes distributed across 7 datacenters. I will also discuss a recent extension, Resilient Canopus, that makes Canopus Byzantine Fault Tolerant.
(Joint work with Sajjad Rizvi and Bernard Wong at the University of Waterloo)