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Aurora: Leaderless State-Machine Replication With High Throughput
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DOI：10.1109/TC.2025.3540656.png)
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Abstract
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State-machine replication (SMR) allows a deterministic state machine to be replicated across a set of replicas and handle clients' requests as a single machine. Most existing SMR protocols are leader-based requiring a leader to order requests and coordinate the protocol. This design places a disproportionately high load on the leader, inevitably impairing the scalability. If the leader fails, a complex and bug-prone fail-over protocol is needed to switch to a new leader. An adversary can also exploit the fail-over protocol to slow down the protocol. In this paper, we propose a crash-fault tolerant SMR named Aurora, with the following properties: center dot Leaderless: it does not require a leader, hence completely get rid of the fail-over protocol. Scalable: it can scale up to 11 replicas. Robust: it behaves well even under a poor network connection. We provide a full-fledged implementation of Aurora and systematically evaluate its performance. Our benchmark results show that Aurora achieves a throughput of around two million Transactions Per Second (TPS), up to 8.7x higher than the state-of-the-art leaderless SMR.
Keywords:
Magnetosphere
Ion radiation effects
Delays
Throughput
Consensus protocol
Proposals
Computers
Training
Switches
Scalability
Crash fault-tolerance
state machine replication
distributed systems
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