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Information Theory of Blockchain Systems
In this paper, we apply the information theory to provide an approximate
expression of the steady-state probability distribution for blockchain systems.
We achieve this goal by maximizing an entropy function subject to specific
constraints. These constraints are based on some prior information, including
the average numbers of transactions in the block and the transaction pool,
respectively. Furthermore, we use some numerical experiments to analyze how the
key factors in this approximate expression depend on the crucial parameters of
the blockchain system. As a result, this approximate expression has important
theoretical significance in promoting practical applications of blockchain
technology. At the same time, not only do the method and results given in this
paper provide a new line in the study of blockchain queueing systems, but they
also provide the theoretical basis and technical support for how to apply the
information theory to the investigation of blockchain queueing networks and
stochastic models more broadly.Comment: 14 pages, 5 figure
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