比特币矿工交易费收入最大化的最优区块

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Mohsen Alambardar Meybodi, Amir Goharshady, Mohammad Reza Hooshmandasl, Ali Shakiba
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引用次数: 0

摘要

在这项工作中,我们考虑了一个直接应用于区块链挖矿的组合优化问题,即为比特币矿工找到最有利可图的区块,并提出了最优算法解决方案。我们的实验表明,我们的算法每月为矿工增加了100多万美元的收入。现代区块链以两种方式奖励矿工:(i)每个被开采的区块的基本奖励,以及(ii)被开采区块中包含的交易的交易费用。基本奖励由各自的区块链协议固定,不受矿工控制。因此,对于希望最大化收益的矿工来说,根本问题是形成一个具有最大总交易费用的有效区块,然后尝试挖掘它。此外,在许多协议中,包括比特币本身,基础奖励在预定间隔减半,因此增加了最大化交易费用和挖掘最佳区块的重要性。由于交易可能是彼此的先决条件或存在冲突(在双重支出的情况下),这个问题变得更加复杂。在这项工作中,我们考虑了在给定一组未挖掘交易的情况下形成一个最优块的问题,即一个具有最大总交易费用的有效块。在理论方面,我们首先将我们的问题正式建模为backpack的扩展,然后证明,与经典的backpack不同,我们的问题是强np困难的。我们也给出了一个近似硬度的结果。因此,对于一般情况,没有希望有效地解决它。然而,我们观察到它的实际实例非常稀疏,即事务具有非常少的依赖关系和冲突。利用这一事实,并利用三个众所周知的图稀疏性参数,即树深、树宽和路径宽度,我们提出了适用于现实世界实例的精确线性时间参数化算法,并获得了最佳结果。在实践方面,我们提供了广泛的实验评估,证明我们的方法在实践中大大优于当前的比特币矿工,每个区块的交易费用收入平均增长11.34%,相当于每月近100万美元。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal blocks for maximizing the transaction fee revenue of Bitcoin miners

In this work, we consider a combinatorial optimization problem with direct applications in blockchain mining, namely finding the most lucrative blocks for Bitcoin miners, and propose optimal algorithmic solutions. Our experiments show that our algorithms increase the miners’ revenues by more than a million dollars per month. Modern blockchains reward their miners in two ways: (i) a base reward for each block that is mined, and (ii) the transaction fees of those transactions that are included in the mined block. The base reward is fixed by the respective blockchain’s protocol and is not under the miner’s control. Hence, for a miner who wishes to maximize earnings, the fundamental problem is to form a valid block with maximal total transaction fees and then try to mine it. Moreover, in many protocols, including Bitcoin itself, the base reward halves at predetermined intervals, hence increasing the importance of maximizing transaction fees and mining an optimal block. This problem is further complicated by the fact that transactions can be prerequisites of each other or have conflicts (in case of double-spending). In this work, we consider the problem of forming an optimal block, i.e. a valid block with maximal total transaction fees, given a set of unmined transactions. On the theoretical side, we first formally model our problem as an extension of Knapsack and then show that, unlike classical Knapsack, our problem is strongly NP-hard. We also show a hardness-of-approximation result. As such, there is no hope in solving it efficiently for general instances. However, we observe that its real-world instances are quite sparse, i.e. the transactions have very few dependencies and conflicts. Using this fact, and exploiting three well-known graph sparsity parameters, namely treedepth, treewidth and pathwidth, we present exact linear-time parameterized algorithms that are applicable to the real-world instances and obtain optimal results. On the practical side, we provide an extensive experimental evaluation demonstrating that our approach vastly outperforms the current Bitcoin miners in practice, obtaining a significant per-block average increase of 11.34 percent in transaction fee revenues which amounts to almost one million dollars per month.

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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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