Dynamic Selection of Mining Pool with Different Reward Sharing Strategy in Blockchain Networks

Abstract

In a PoW-based blockchain network, miners participate in a block-discovery racing game for financial incentives. As the total computing power becomes overwhelming, miners join in the mining pool which combines the scattered computing power to win a stable profit. Miners in the same mining pool work as a team and once they successfully mine a valid block, mining pool plays a role in distributing the payoff to miners according to its reward sharing mechanism. Specifically, two main reward sharing strategies: Pay-Per-Share (PPS) and Pay-Per-Last-NShare (PPLNS) are considered. In the mining system model, a miner can choose to join a pool and adapt the selection for improving the expected reward. And we formulate the dynamic pool selection problem as an evolutionary game. We consider the required hash rate, network delay and reward sharing strategy as the main factors which affect the choice of miners. Evolutionary stable equilibrium (ESS) is considered to be the solution, and we conduct theoretical analysis on the existence and stability of the ESS for a case of two mining pools. A low complexity distributed algorithm is proposed for miners to reach the equilibrium. Numerical results show the evolution of miners and demonstrate the theoretical findings of our study.