  Consensus, state-machine replication (SMR) and total order broadcast (TOB)
protocols are notorious for being poorly scalable with the number of
participating nodes. Despite the recent race to reduce overall message
complexity of leader-driven SMR/TOB protocols, scalability remains poor and the
throughput is typically inversely proportional to the number of nodes. We
present Insanely Scalable State-Machine Replication, a generic construction to
turn leader-driven protocols into scalable multi-leader ones. For our scalable
SMR construction we use a novel primitive called Sequenced (Total Order)
Broadcast (SB) which we wrap around PBFT, HotStuff and Raft leader-driven
protocols to make them scale. Our construction is general enough to accommodate
most leader-driven ordering protocols (BFT or CFT) and make them scale. Our
implementation improves the peak throughput of PBFT, HotStuff, and Raft by 37x,
56x, and 55x, respectively, at a scale of 128 nodes.

Distributed, Parallel, and Cluster Computing