Genetic-Algorithm-Inspired Difficulty Adjustment for Proof-of-Work Blockchains

Zi Hau Chin, Timothy Tzen Vun Yap*, Ian Kim Teck Tan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
102 Downloads (Pure)

Abstract

In blockchains, the principle of proof-of-work (PoW) is used to compute a complex mathematical problem. The computation complexity is governed by the difficulty, adjusted periodically to control the rate at which new blocks are created. The network hash rate determines this, a phenomenon of symmetry, as the difficulty also increases when the hash rate increases. If the hash rate grows or declines exponentially, the block creation interval cannot be maintained. A genetic algorithm (GA) is proposed as an additional mechanism to the existing difficulty adjustment algorithm for optimizing the blockchain parameters. The study was conducted with four scenarios in mind, including a default scenario that simulates a regular blockchain. All the scenarios with the GA were able to achieve a lower standard deviation of the average block time and difficulty compared to the default blockchain network without GA. The scenario of a fixed difficulty adjustment interval with GA was able to reduce the standard deviation of the average block time by 80.1%, from 497.1 to 98.9, and achieved a moderate median block propagation time of 6.81 s and a stale block rate of 6.67%.

Original languageEnglish
Article number609
JournalSymmetry
Volume14
Issue number3
DOIs
Publication statusPublished - 18 Mar 2022

Keywords

  • blockchain
  • difficulty adjustment
  • genetic algorithm
  • proof-of-work

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Chemistry (miscellaneous)
  • General Mathematics
  • Physics and Astronomy (miscellaneous)

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