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 ${\mathcal{O}}\left({{n^2}}\right)$ 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.