JUNO: Aggregated Vector Consensus for Optimal Asynchronous Common Subset

In this paper, we propose aggregated vector consensus, a new vector consensus primitive designed for asynchronous networks. The primitive achieves agreement by outputting a vector of values aggregated from independent process inputs. We then introduce Juno, an asynchronous common subset (ACS) protocol that fully implements our aggregated vector consensus to attain optimal O(n 2) message complexity. We further implement and evaluate Juno in comparison with the legacy HoneyBadgerBFT and the state-of-the-art Dory. Experiment results demonstrate its efficacy and efficiency. Our protocol demonstrates an average throughput performance improvement of 93% compared with HoneyBadgerBFT and a 47% improvement compared with Dory. Notably, our study makes significant progress in addressing the gap in applying vector consensus protocol in fully asynchronous networks.