Performance Modeling of Blockchains with Fixed Block Intervals

With the emergence of various application scenarios, various chains have been developed to meet their requirements. Among them, chains with fixed block intervals (fixed chains for short) occupy an increasingly significant position. Performance has always been a key bottleneck of blockchains and modeling for them is the most common method for performance analysis. But til now, few models for fixed chains exist and they are not precise and applicable enough. This paper proposes a model for fixed chains via the bulk-service queuing theory, which can reflect the real scenario more precisely and apply to the high load. We consider the continuous time and the transaction (TX for short) pool with limited capacity and reflect the chains’ features of fixed intervals and empty blocks to improve accuracy and applicability. We give an expression for three significant measurements: the average confirmation delay of TXs, the blockchain throughput, and the TX rejection rate. We use Ethereum to validate our model. And moreover, we use the model for analysis to assist designers in operating chains.