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This well-studied model gives mathematical insights in the mempool behaviour over time. Specifically, for situations where one chooses a fee, such that the total size of incoming transactions with higher fee is close to the total size of transactions leaving the mempool (heavy traffic), a diffusion approximation leads to an inverse Gaussian distribution for the confirmation times. The results of this paper are particularly interesting for users that want to make a Bitcoin transaction during heavy-traffic situations, as evaluation of the well-known inverse Gaussian distribution is computationally straightforward.<\/jats:p>","DOI":"10.1145\/3466826.3466833","type":"journal-article","created":{"date-parts":[[2021,5,19]],"date-time":"2021-05-19T16:09:27Z","timestamp":1621440567000},"page":"16-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Predicting confirmation times of Bitcoin transactions"],"prefix":"10.1145","volume":"48","author":[{"given":"Rowel","family":"Gundlach","sequence":"first","affiliation":[{"name":"Eindhoven University of Technology, Eindhoven, Netherlands"}]},{"given":"Martijn","family":"Gijsbers","sequence":"additional","affiliation":[{"name":"Eindhoven University of Technology, Eindhoven, Netherlands"}]},{"given":"David","family":"Koops","sequence":"additional","affiliation":[]},{"given":"Jacques","family":"Resing","sequence":"additional","affiliation":[{"name":"Eindhoven University of Technology, Eindhoven, Netherlands"}]}],"member":"320","published-online":{"date-parts":[[2021,5,19]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_2_1_1_1","DOI":"10.1142\/7431"},{"key":"e_1_2_1_2_1","volume-title":"Cryptocurrencies: A brief thematic review. 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An introduction to Bitcoin core fee estimation."},{"doi-asserted-by":"publisher","key":"e_1_2_1_12_1","DOI":"10.1016\/S0167-6687(98)00025-0"},{"doi-asserted-by":"publisher","key":"e_1_2_1_13_1","DOI":"10.2143\/AST.29.2.504613"},{"doi-asserted-by":"publisher","key":"e_1_2_1_14_1","DOI":"10.2307\/1426855"}],"container-title":["ACM SIGMETRICS Performance Evaluation Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3466826.3466833","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3466826.3466833","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:28:09Z","timestamp":1750195689000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3466826.3466833"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,17]]},"references-count":14,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,5,17]]}},"alternative-id":["10.1145\/3466826.3466833"],"URL":"https:\/\/doi.org\/10.1145\/3466826.3466833","relation":{},"ISSN":["0163-5999"],"issn-type":[{"type":"print","value":"0163-5999"}],"subject":[],"published":{"date-parts":[[2021,5,17]]},"assertion":[{"value":"2021-05-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}