MODELING OF THE MEMPOOL SIZE CHANGE BASED ON THE MONTE CARLO METHOD UNDER CONDITIONS OF INCOMPLETE INITIAL INFORMATION
Abstract
This article examines the influence of various parameters of the blockchain network on each other. Due to the mathematical complexity of forming an absolutely accurate emulator of the block chain formation process and the unpredictability of a number of factors, the process is considered stochastic. The study found a close to directly proportional relationship between the size of the mempool and the value of the cryptocurrency. A mempool is a set of transactions awaiting confirmation on the blockchain. The cost of cryptocurrency can affect the number of miners processing transactions, attracting them with high earnings, which can affect the speed of transaction processing and, as a result, the size of the mempool. The paper describes the application of the Monte Carlo method to determine the ratio between the size of a mempool and the price of a cryptocurrency, as well as the preliminary preparation of data and the formation of distributions. A stochastic process simulation is described to determine the relationship between the size of a mempool and the price of a cryptocurrency. To do this, the Monte Carlo method is used, which allows you to estimate the probability of various scenarios. The paper considers various stochasticmodels for the analysis of blockchain systems, for the construction of which the Monte Carlo method is used. The author proposes a methodology for predicting and establishing a correlation between the parameters under consideration based on data collected from the BitCoin network over the past three years. The results of the study confirmed the hypothesis that there is a relationship between the value of cryptocurrency and the volume of unprocessed transactions. Due to the lack of a complete data set, it remains impossible to predict the load on the network at a specific cost. A solution to this problem was presented using probabilistic methods, including the Monte Carlo method, based on the distribution of the historical data obtained. Using the Monte Carlo method to model the relationship between the size of a mempool and the price of a cryptocurrency and other similar tasks in similar conditions can be a useful tool for researchers to draw conclusions about the stable operation of the network
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