Measurement and Analysis of the Bitcoin Networks: A View from Mining Pools

Abstract

has received much attention from both industry and the academy. 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., empty blocks, mining revenue and transaction collection strategies) 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 1.56 hundred thousand blocks (including about 257 million historical transactions) from February 2016 to January 2019 and collected over 120.25 million unconfirmed transactions from March 2018 to January 2019. 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 show the following. 1) A few mining pools entities continuously control most of the computing resources of the Bitcoin network. 2) Mining pools are 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 are 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 are not sensitive to the event of halving block rewards. 5) The block interval of empty blocks is significantly lower than the block interval of non-empty blocks. 6) Feerate plays a dominating role in transaction collection strategy for the top mining pools. Our measurements and analysis help to understand and improve the Bitcoin network.

Measuring Decentralization in Bitcoin and Ethereum using Multiple Metrics and Granularities

“…Most of the recent works on decentralization in blockchain have focused on Bitcoin [3], [4], [6], [12], [19]. These works pointed out that Bitcoin shows a trend towards centralization because of the emergence of mining pools.…”

“…Later, authors in [3] analyzed the mining competitions among mining pools in Bitcoin from the perspective of game theory and proposed that a rational mining pool may get incentivized to launch a block withholding attack to another mining pool. From the perspective of mining pools, authors in [19] tracked more than 1.56 million blocks (including about 257 million historical transactions) and found that a few mining pools was controlling and will keep controlling most of the computing resources of the Bitcoin network. Through the research of a small fraction of the network, authors in [12] found that the nodes connected with the major mining pools occupy higher mining capacity.…”

XBlock-ETH: Extracting and Exploring Blockchain Data From Ethereum

“…However, there are few studies on the decentralization evaluation of the blockchain systems. In particular, the work of [16] presents the measurement of the mining pool for Bitcoin. Although Gencer et al [17] present a measurement study on the decentralization level of Bitcoin and Ethereum, their study only consider several metrics such as network bandwith, mining power and fairness.…”

XBlock-EOS: Extracting and Exploring Blockchain Data From EOSIO

“…However, there are few studies on the decentralization evaluation of different blockchain systems, especially for DPoS-based EOSIO. In the study [33], Wang et al proposed a measurement study for the Bitcoin mining pool. In addition, Gencer et al proposed a measurement study on the decentralization level of the Bitcoin and Ethereum networks [34].…”