On-Chain Governance Model Based on Particle Swarm Optimization for Reducing Blockchain Forks

In my research, I explore how technology is changing economic forces. I focus on blockchain technologies and platform competition. In both these areas, we see that technology has challenged the underlying foundations of business, and firms must evaluate and change their strategies accordingly. My findings indicate that conventional wisdom and rules of thumb derived from standard economic analysis may provide insufficient guidance to firms in technology-focused industries.

Blockchain technology has emerged as one of the most promising technologies in the past few years. However, it has encountered a number of challenges, including forks and low processing rates when compared to other systems relating to payments. Despite that it is natural for most public blockchain systems to fork over time, the side fork transactions will be discarded during chain reorganization (reorg). As a result, clients need to wait for more confirmations before completing transactions and experience a slight delay in the process. The probability of a blockchain network forking to the greatest extent possible should be minimized, as it will improve the security, speed, and efficiency of the blockchain network. In this research, we propose a novel fork model that incorporates previously unconsidered parameters, such as the network delay and degree of validation. We conducted a series of experiments using a blockchain simulator on the Ethereum network and the EIP-1559 specification to verify the validity of our proposed method, andfound that a fork is less likely to occur by approximately 10% if the validation degree is decreased and the marginal cost of the miners is increased (as in EIP-1559). Further, the results of our experiment demonstrate that our method is highly accurate in predicting forking probabilities.