CRJul 1, 2021
Stochastic Performance Modeling for Practical Byzantine Fault Tolerance Consensus in BlockchainFan-Qi Ma, Quan-Lin Li, Yi-Han Liu et al.
The practical Byzantine fault tolerant (PBFT) consensus mechanism is one of the most basic consensus algorithms (or protocols) in blockchain technologies, thus its performance evaluation is an interesting and challenging topic due to a higher complexity of its consensus work in the peer-to-peer network. This paper describes a simple stochastic performance model of the PBFT consensus mechanism, which is refined as not only a queueing system with complicated service times but also a level-independent quasi-birth-and-death (QBD) process. From the level-independent QBD process, we apply the matrix-geometric solution to obtain a necessary and sufficient condition under which the PBFT consensus system is stable, and to be able to numerically compute the stationary probability vector of the QBD process. Thus we provide four useful performance measures of the PBFT consensus mechanism, and can numerically calculate the four performance measures. Finally, we use some numerical examples to verify the validity of our theoretical results, and show how the four performance measures are influenced by some key parameters of the PBFT consensus. By means of the theory of multi-dimensional Markov processes, we are optimistic that the methodology and results given in this paper are applicable in a wide range research of PBFT consensus mechanism and even other types of consensus mechanisms.
CRApr 7, 2019
Markov Processes in Blockchain SystemsQuan-Lin Li, Jing-Yu Ma, Yan-Xia Chang et al.
In this paper, we develop a more general framework of block-structured Markov processes in the queueing study of blockchain systems, which can provide analysis both for the stationary performance measures and for the sojourn times of any transaction and block. Note that an original aim of this paper is to generalize the two-stage batch-service queueing model studied in Li et al. \cite{Li:2018} both ``from exponential to phase-type" service times and ``from Poisson to MAP" transaction arrivals. In general, the MAP transaction arrivals and the two stages of PH service times make our blockchain queue more suitable to various practical conditions of blockchain systems with crucial random factors, for example, the mining processes, the block-generations, the blockchain-building and so forth. For such a more general blockchain queueing model, we focus on two basic research aspects: (1) By using the matrix-geometric solution, we first obtain a sufficient stable condition of the blockchain system. Then we provide simple expressions for the average number of transactions in the queueing waiting room, and the average number of transactions in the block. (2) However, comparing with Li et al. \cite{Li:2018}, analysis of the transaction-confirmation time becomes very difficult and challenging due to the complicated blockchain structure. To overcome the difficulties, we develop a computational technique of the first passage times by means of both the PH distributions of infinite sizes and the $RG$-factorizations. Finally, we hope that the methodology and results given in this paper will open a new avenue to queueing analysis of more general blockchain systems in practice, and can motivate a series of promising future research on development of lockchain technologies.