Parallel BFT instances describe a system architecture where multiple independent instances of a Byzantine Fault Tolerant (BFT) consensus algorithm operate simultaneously. Each instance validates and orders a distinct subset of transactions or data. This parallelization significantly boosts overall network throughput by distributing the workload among several consensus groups. It maintains strong security guarantees across the entire system.
Context
Parallel BFT instances are a key component in advanced blockchain designs, particularly those focused on achieving horizontal scalability through sharding. Discussions often center on the complex challenges of coordinating these multiple instances and ensuring consistent state across shards. A critical future development involves the successful deployment of these architectures to overcome the performance limitations of single-threaded consensus mechanisms, enabling much higher transaction volumes.
The HYDRA framework introduces object-centric execution to parallelize BFT instances, fundamentally removing the global ordering bottleneck and unlocking true consensus scalability.
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