Abstract
Pooled mining is the de facto mining pattern in public, PoW (Proof of Work) based blockchain systems like Bitcoin and Ethereum. Mining pool aggregates discrete miners’ computation power to improve probability of getting the right block, and stabilize miners’ rewards. Miners reach consensus among pools, and maintain the whole blockchain network's stability. Due to architecture constrains across underlying transmission mechanism, computation power differences among nodes, and consensus algorithms, mining pools are facing increasing performance challenges, which lead to wastes of computing resources and loss of miners’ rewards. Based on analysis of mining pool architecture, this paper proposed a numerical model MENM (Miner Efficiency Numerical Model) to measure miner's computing efficiency, and a performance tuning mechanism DDCT (Dynamic Difficulty Calculation and Tuning) to dynamically adjust individual miner's difficulty in a pool based on MENM value, to improve mining pool's efficiency. The proposed tuning mechanism is also tested against a small experimental PoW mining pool to validate its effect.
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