Title | A General Difficulty Control Algorithm for Proof-of-Work Based Blockchains |

Publication Type | Conference Paper |

Year of Publication | 2020 |

Authors | Zhang, S., Ma, X. |

Conference Name | ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |

Keywords | block difficulty, blockchain, compositionality, cryptography, Data models, difficulty adjustment rules, difficulty control algorithm, efficient difficulty control algorithm, general difficulty control algorithm, hash algorithms, hash rate, Memory management, network hash rate, neural nets, Neural networks, PoW based blockchains, Proof-of-Work based blockchains, pubcrawl, Resiliency, Signal processing, Signal processing algorithms, speech processing, two-layer neural network |

Abstract | Designing an efficient difficulty control algorithm is an essential problem in Proof-of-Work (PoW) based blockchains because the network hash rate is randomly changing. This paper proposes a general difficulty control algorithm and provides insights for difficulty adjustment rules for PoW based blockchains. The proposed algorithm consists a two-layer neural network. It has low memory cost, meanwhile satisfying the fast-updating and low volatility requirements for difficulty adjustment. Real data from Ethereum are used in the simulations to prove that the proposed algorithm has better performance for the control of the block difficulty. |

DOI | 10.1109/ICASSP40776.2020.9054286 |

Citation Key | zhang_general_2020 |