Leveraging Towards Analytical Approach of Fixed batch-based Queueing assisted Blockchain System

Abstract

Bitcoin is a virtual cryptocurrency built on the blockchain, a transaction-ledger database. The blockchain is updated and maintained by a miner passing through a mining process in which a group of miners competes to solve a tough puzzle-like challenge. Users’ transactions are grouped into blocks, and when an algorithmic problem specialized for the block is solved, the block is recorded to the blockchain. According to a recent study, newly arrived transactions are not included in the block being mined and waits in the unconfirmed transaction pool and mined by a miner till the number of transaction matches a minimum batch size i.e. the block size limit. The transaction-confirmation time is investigated in this paper by simulating the mining process using a queueing system with batch service. We assume a Markovian queue that processes transactions in fixed batch K. Additionally, we evaluate the model’s performance metrics, such as the estimated number of transactions seeking to enter the block from the queue, the mean number of transactions waiting in the unconfirmed transaction pool, the waiting time for a transaction, and the confirmation time for every transaction. The validation of the analytical model was performed utilizing the software packages MAPLE 18 to analyze the conclusions acquired by the queueing model.