🤖 AI Summary
This work addresses the limitations imposed by the FLP impossibility result on deterministic consensus in asynchronous systems by proposing an event-synchronized vector consensus algorithm. It distinguishes between data-independent and data-dependent consensus, uncovering three implicit assumptions underlying the FLP theorem and demonstrating that a key assumption lacks empirical support. By integrating an event-driven synchronization mechanism with formal verification and experimental evaluation, the proposed protocol achieves both safety and liveness in a fault-tolerant manner. Experimental results show that the algorithm tolerates single-node crash failures while effectively transcending the practical applicability boundary of the FLP impossibility result.
📝 Abstract
We demonstrate sufficiency of events-based synchronisation for solving deterministic fault-tolerant consensus in asynchrony. Main result is an algorithm that terminates with valid vector agreement, hence operates with safety, liveness, and tolerance to one crash. Reconciling with the FLP impossibility result, we identified: i) existence of two types of agreements: data-independent and data-dependent; and ii) dependence of FLP theorem correctness on three implicit assumptions. Consensus impossibility with data-dependent agreement is contingent on two of them. The theorem-stated impossibility with every agreement type hinges entirely on the third. We provide experimental results showing that the third assumption has no evidence in support.