Fast Probabilistic Consensus with Weighted Votes

TL;DR

This paper adapts the Fast Probabilistic Consensus protocol to weighted voting based on node reputation, demonstrating improved robustness and efficiency through simulations and strategic adversary detection methods.

Contribution

It introduces a reputation-based weighting scheme for FPC, models reputation with Zipf law, and proposes enhancements to reduce failure rates and detect malicious strategies.

Findings

Performance improves with higher Zipf exponent

Failure rates decrease with proposed protocol improvements

Effective detection of harmful adversarial strategies

Abstract

The fast probabilistic consensus (FPC) is a voting consensus protocol that is robust and efficient in Byzantine infrastructure. We propose an adaption of the FPC to a setting where the voting power is proportional to the nodes reputations. We model the reputation using a Zipf law and show using simulations that the performance of the protocol in Byzantine infrastructure increases with the Zipf exponent. Moreover, we propose several improvements of the FPC that decrease the failure rates significantly and allow the protocol to withstand adversaries with higher weight. We distinguish between cautious and berserk strategies of the adversaries and propose an efficient method to detect the more harmful berserk strategies. Our study refers at several points to a specific implementation of the IOTA protocol, but the principal results hold for general implementations of reputation models.