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Sleepy Consensus in the Known Participation Model
Authors: Chenxu Wang, Sisi Duan, Minghui Xu, Feng Li, Xiuzhen ChengAbstract:
We study sleepy consensus in the known participation model, where replicas are aware of the minimum number of awake honest replicas. Compared to prior works that almost all assume the unknown participation model, we provide a fine-grained treatment of sleepy consensus in the known participation model and show some interesting results. First, we present a synchronous atomic broadcast protocol with 5\Delta+2\delta expected latency and 2\Delta+2\delta best-case latency, where \Delta is the bound on network delay and \delta is the actual network delay. In contrast, the best-known result in the unknown participation model (MMR, CCS 2023) achieves 14\Delta latency, more than twice the latency of our protocol. Second, in the partially synchronous network (the value of \Delta is unknown), we show that without changing the conventional n \geq 3f+1 assumption, one can only obtain a secure sleepy consensus by making the stable storage assumption (where replicas need to store intermediate consensus parameters in stable storage). Finally, still in the partially synchronous network but not assuming stable storage, we prove the bounds on n \geq 3f+2s+1 without the global awake time (GAT) assumption (all honest replicas become awake after GAT) and n \geq 3f+s+1 with the GAT assumption, where s is the maximum number of honest replicas that may become asleep simultaneously. Using these bounds, we transform HotStuff (PODC 2019) into a sleepy consensus protocol via a timeoutQC mechanism and a low-cost recovery protocol.
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