• On Optimizing Transaction Fees in Bitcoin using AI: Investigation on Miners Inclusion Pattern 

      Tedeschi, Enrico; Nordmo, Tor-Arne Schmidt; Johansen, Dag; Johansen, Håvard D. (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-09)
      The transaction-rate bottleneck built into popular proof-of-work-based cryptocurrencies, like Bitcoin and Ethereum, leads to fee markets where transactions are included according to a first-price auction for block space. Many attempts have been made to adjust and predict the fee volatility, but even well-formed transactions sometimes experience unexpected delays and evictions unless a substantial ...
    • Predicting Transaction Latency with Deep Learning in Proof-of-Work Blockchains 

      Tedeschi, Enrico; Nordmo, Tor-Arne Schmidt; Johansen, Dag; Johansen, Håvard D. (Peer reviewed; Chapter, 2019)
      Proof-of-work based cryptocurrencies, like Bitcoin, have a fee market where transactions are included in the blockchain according to a first-price auction for block space. Many attempts have been made to adjust and predict the fee volatility, but even well-formed transactions sometimes experience delays and evictions unless an enormous fee is paid. % In this paper, we present a novel ...
    • Trading network performance for cash in the bitcoin blockchain 

      Tedeschi, Enrico (Master thesis; Mastergradsoppgave, 2017-11-15)
      This thesis describes a longitudinal study of Bitcoin, the perhaps most popular blockchain based system today. Public blockchains have emerged as a plausible messaging substrate for applications that require highly reliable communication. However, sending messages over existing blockchains can be cumbersome and costly as miners require payment to establish consensus on the sequence of messages, ...