【Author】
Wang, Canhui; Chu, Xiaowen; Qin, Yang
【Source】2020 6TH INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING AND COMMUNICATIONS (BIGCOM 2020)
【Abstract】Bitcoin network has received much attention from both industry and academy due to Bitcoin's recent success. Mining pools, the main components of the Bitcoin network, dominate the computing resources, and play essential roles in network security and performance aspects. Although many existing measurements of the Bitcoin network are available, little is known about the details of mining pool behaviors (e.g., mining revenue and transaction collection strategy) and their effects on the Bitcoin end users (e.g., transaction fees, transaction delay, and transaction acceptance rate). This paper aims to fill this gap with a systematic study of mining pools. We traced over 2.15 hundred thousand blocks from February 2016 to February 2020 and collected over 4.12 TB unconfirmed transactions. Then we conducted a board range of measurements on the pool evolutions, labeled transactions (blocks) as well as real-time network traffics, and discovered new interesting observations and features. Specifically, our measurements showed the following. 1) A few mining pools continuously controlled most of the computing resources of the Bitcoin network. 2) Mining pools were caught in a prisoner's dilemma where mining pools compete to increase their computing resources even though the unit profit of the computing resource decreases. 3) Mining pools were stuck in a Malthusian trap where there is a stage at which the Bitcoin incentives are inadequate for feeding the exponential growth of the computing resources. 4) The market price and transaction fees were not sensitive to the past events of halving block rewards. 5) Feerate played a dominating role in the transaction collection strategy for the top mining pools. Our measurements and analysis helped the Bitcoin community to understand and improve the Bitcoin network.
【Keywords】Bitcoin Network; Mining Pools; Malthusian Trap; Incentive Mechanism
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