Author:
Rudrapana K. Shyamasundar
Affiliation:
Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
Keyword(s):
Blockchain, POW, POS, Consensus, Correctness, Forking.
Abstract:
Ripple network or the XRP network is one of the most versatile blockchain platforms used worldwide for payment systems, healthcare applications etc. The abstract protocol called XRP ledger consensus protocol (XRPL for short) is a refined version of the initial design referred to as Ripple Protocol consensus algorithm (RPCA). It is based on the Byzantine fault-tolerant (BFT) agreement protocol but does not use the standard models or implementation but utilizes collectively-trusted sub-networks within a large network. Consensus is achieved by maintaining a certain level of “trust” for the sub-networks and a certain minimal connectivity throughout the network so that the network can be robust in the face of Byzantine failures. For each server in the XRP network called there is sub-network of validators, referrred to as the Unique Node List (UNL) consisting of a subset of the servers of the whole network. To be robust against Byzantine failures, XRPL enforces 80% quorum and a certain ove
rlap of nodes across the UNLs. The overlap was initially specified to be 20% and was later enhanced to be greater than 90% to satisfy conditions of safety and liveness. However, even with such an enhancement, safety and liveness are not satisfied. In this paper, we characterize, the XRP Ledger Consensus protocol (abbreviated XRPL) for consensus correctness using a notion of similarity metric called rand-index (RI) used for cluster analysis of networks. We establish that XRPL with 80% quorum and UNLs satisfying 50% RI similarity, is robust against 20% failures, that is, no fraudulent transactions will be accepted by the network. Further, the network satisfies consensus correctness if the UNLs of the network are more than 50% RI similar that would imply at least 80% quorum across all the UNLs.
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