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


Chin, Zi Hau and Yap, Timothy Tzen Vun and Tan, Ian Kim Teck (2022) Genetic-Algorithm-Inspired Difficulty Adjustment for Proof-of-Work Blockchains. Symmetry, 14 (3). p. 609. ISSN 2073-8994

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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%.

Item Type: Article
Uncontrolled Keywords: Blockchain, difficulty adjustment, genetic algorithm
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 27 Jul 2022 00:53
Last Modified: 27 Jul 2022 00:53


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