使用基于遗传算法的工作量证明的高效比特币挖掘

S. Mehta, M. Goyal, D. Saini
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引用次数: 0

摘要

区块链需要通过矿工从未确认的交易池中确认交易来验证区块。矿工们从大约2000多笔未经确认的交易池中提取交易,并在有限的时间内解决算法难题,即也称为工作量证明。为了最大限度地提高每秒的吞吐量,需要优化时间段来解决验证块的算法难题。传统上,对于未经确认的交易,矿工使用蛮力算法解决工作量证明,由于计算量巨大,消耗大量电能。为了优化区块链挖掘的时间,本文提出了一种基于遗传算法的区块挖掘(GAMB)方法,从未经确认的交易池中提取交易,以便在有限的时间内验证区块。它是一种基于人口的算法,试图并行解决多个事务的工作量证明。GAMB的性能是针对1000到5000个事务进行评估的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Bitcoin Mining Using Genetic Algorithm-Based Proof of Work
Blockchain requires to validate the block with confirmed transactions from the unconfirmed pool of transactions through Miners. Miners pick up the transactions from the pool of unconfirmed transactions approximately more than 2000 and solve the algorithmic puzzle i.e. also known as proof of work within the limited period of time. To maximize the throughput per second requires optimization of the time period to solve the algorithm puzzle for validating the block. Conventionally, for unconfirmed transactions, miners solve the proof of work using brute force algorithms which consume a lot of electrical energy due to the huge number of computations. To optimize the time for block chain mining, this paper proposes a Genetic algorithm based block mining (GAMB) approach to fetch the transactions from the unconfirmed pool of transactions in order to validate the block within a limited period of time. It is a population based algorithm which attempts to solve the proof of work for multiple transactions in parallel. The performance of GAMB is evaluated for transactions from 1000 to 5000.
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