Model-based Analysis of Mining Fairness in a Blockchain

Mining fairness in blockchain refers to equality between the computational resources invested in mining and the block rewards received. There exists a dilemma wherein increasing the transaction processing capacity of a blockchain compromises mining fairness, which consequently undermines its decentralization. This dilemma remains unresolved even with methods such as the greedy heaviest observed subtree (GHOST) protocol, indicating that mining fairness is an inherent bottleneck in the transaction processing capacity of the blockchain system. However, despite its significance, there have been insufficient research studies that have quantitatively analyzed mining fairness. In this paper, we propose a method for calculating mining fairness. First, we approximated a complex blockchain network using a simple mathematical model, assuming that no more than two blocks are generated per round. Within this model, we quantitatively determined local mining fairness and derived several measures of global mining fairness based on local mining fairness. Subsequently, we validated by blockchain network simulations that our calculation method computes mining fairness in networks much more accurately than existing methods. Finally, we analyzed various networks from the perspective of mining fairness.

@article{sakurai2025_2406.00595,
  title={ Model-based Analysis of Mining Fairness in a Blockchain },
  author={ Akira Sakurai and Kazuyuki Shudo },
  journal={arXiv preprint arXiv:2406.00595},
  year={ 2025 }
}