Stability analysis and control of decision-making of miners in blockchain
This work addresses security and service maintenance in blockchain systems by stabilizing miner decision-making, but it is incremental as it applies existing game theory methods to this specific domain.
The paper tackles the problem of setting mining rewards to increase miner participation in blockchain networks, using a dynamical model based on evolutionary game theory to analyze stability and design a controller that stabilizes full participation, with numerical simulations revealing trade-offs in parameter choices.
To maintain blockchain-based services with ensuring its security, it is an important issue how to decide a mining reward so that the number of miners participating in the mining increases. We propose a dynamical model of decision-making for miners using an evolutionary game approach and analyze the stability of equilibrium points of the proposed model. The proposed model is described by the 1st-order differential equation. So, it is simple but its theoretical analysis gives an insight into the characteristics of the decision-making. Through the analysis of the equilibrium points, we show the transcritical bifurcations and hysteresis phenomena of the equilibrium points. We also design a controller that determines the mining reward based on the number of participating miners to stabilize the state that all miners participate in the mining. Numerical simulation shows that there is a trade-off in the choice of the design parameters.