V. Goswami, B. B. Dash, S. Tripathy, Barun Bikram Dash, S. Patra, Rabindra Kumar Barik
{"title":"对基于固定批处理的排队辅助区块链系统分析方法的借鉴","authors":"V. Goswami, B. B. Dash, S. Tripathy, Barun Bikram Dash, S. Patra, Rabindra Kumar Barik","doi":"10.1145/3549206.3549247","DOIUrl":null,"url":null,"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.","PeriodicalId":199675,"journal":{"name":"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Leveraging Towards Analytical Approach of Fixed batch-based Queueing assisted Blockchain System\",\"authors\":\"V. Goswami, B. B. Dash, S. Tripathy, Barun Bikram Dash, S. Patra, Rabindra Kumar Barik\",\"doi\":\"10.1145/3549206.3549247\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":199675,\"journal\":{\"name\":\"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3549206.3549247\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3549206.3549247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Leveraging Towards Analytical Approach of Fixed batch-based Queueing assisted Blockchain System
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.