Abstract
AbstractIn this paper, the authors propose to increase the efficiency of blockchain mining by using a population-based approach. Blockchain relies on solving difficult mathematical problems as proof-of-work within a network before blocks are added to the chain. Brute force approach, advocated by some as the fastest algorithm for solving partial hash collisions and implemented in Bitcoin blockchain, implies exhaustive, sequential search. It involves incrementing the nonce (number) of the header by one, then taking a double SHA-256 hash at each instance and comparing it with a target value to ascertain if lower than that target. It excessively consumes both time and power. In this paper, the authors, therefore, suggest using an inner for-loop for the population-based approach. Comparison shows that it’s a slightly faster approach than brute force, with an average speed advantage of about 1.67% or 3,420 iterations per second and 73% of the time performing better. Also, we observed that the more the total particles deployed, the better the performance until a pivotal point. Furthermore, a recommendation on taming the excessive use of power by networks, like Bitcoin’s, by using penalty by consensus is suggested.
Highlights
Blockchain, as a digital distributed ledger, implies it’s an electronic, decentralized permanent storage of transactions [1]
Our null hypothesis that there is no difference between the means of brute force and 200-Particle inner forloop (IFL) is tested with statistical analysis of two sample t-test
This research work used the method of comparative study to critically analyze results from several scenarios of the newly implemented inner for-loop program and the widespread brute force algorithm on blockchain mining
Summary
Blockchain, as a digital distributed ledger, implies it’s an electronic, decentralized permanent storage of transactions [1]. Its first successful implementation was as the backbone of a peer to peer network for Bitcoin by Nakamoto [1]. It has no requirement for a central server. Population-based approaches use multiple solutions at the same time [7], such as with genetic algorithms [7, 8] or PSO [9]. Brute force is the widespread implementation, possibly the only approach, to mining blockchain [1, 2]. This research uses the method of comparative study to critically analyze results from several tests of the implemented populationbased algorithm and sequential brute force algorithm. Brute force approach usually uses one loop to iterate over all values and is the most intuitive approach to solving a problem but has very low efficiency in some cases [10]
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