Energy and Resource Consumption in Cryptocurrency Mining: A Detailed Comparison

Gundaboina, Lokesh; Badotra, Sumit; Tanwar, Sarvesh

doi:10.1109/icrito51393.2021.9596387

Cited by 4 publications

(4 citation statements)

References 15 publications

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“…For example, Gundaboina et al. 126 conducted statistical data analysis in a Dogecoin mining benchmark and found that the hashing algorithm determines mining cost. Mining companies are trying to use renewable energy to replace traditional energy and reduce the carbon footprint.…”

Section: Overview Of Cryptocurrencymentioning

confidence: 99%

A survey of deep learning applications in cryptocurrency

Zhang,

Cai,

Wen

2024

iScience

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Section: Overview Of Cryptocurrencymentioning

confidence: 99%

A survey of deep learning applications in cryptocurrency

Zhang,

Cai,

Wen

2024

iScience

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“…Due to the rise of information technology, cryptocurrency is decentralized digital cash that employs encoding to control online transactions. Satoshi Nakamoto [1] introduced Bitcoin, launching the initial cryptocurrency in late 2008 [2]. Despite the very fact that there are about 900 cryptocurrencies [2], Bitcoin has been the foremost thriving digital currency since its launch in 2009 [2].…”

Section: Introductionmentioning

confidence: 99%

“…Satoshi Nakamoto [1] introduced Bitcoin, launching the initial cryptocurrency in late 2008 [2]. Despite the very fact that there are about 900 cryptocurrencies [2], Bitcoin has been the foremost thriving digital currency since its launch in 2009 [2]. Bitcoin may be obtained through acquiring goods, supplying services or exchanging it for alternative currencies [3].…”

Section: Introductionmentioning

confidence: 99%

A Novel Optimization for GPU Mining Using Overclocking and Undervolting

et al. 2022

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Cryptography and associated technologies have existed for a long time. This field is advancing at a remarkable speed. Since the inception of its initial application, blockchain has come a long way. Bitcoin is a cryptocurrency based on blockchain, also known as distributed ledger technology (DLT). The most well-known cryptocurrency for everyday use is Bitcoin, which debuted in 2008. Its success ushered in a digital revolution, and it currently provides security, decentralization, and a reliable data transport and storage mechanism to various industries and companies. Governments and developing enterprises seeking a competitive edge have expressed interest in Bitcoin and other cryptocurrencies due to the rapid growth of this recent technology. For computer experts and individuals looking for a method to supplement their income, cryptocurrency mining has become a big source of anxiety. Mining is a way of resolving mathematical problems based on the processing capacity and speed of the computers employed to solve them in return for the digital currency incentives. Herein, we have illustrated benefits of utilizing GPUs (graphical processing units) for cryptocurrency mining and compare two methods, namely overclocking and undervolting, which are the superior techniques when it comes to GPU optimization. The techniques we have used in this paper will not only help the miners to gain profits while mining cryptocurrency but also solve a major flaw; in order to mitigate the energy and resources that are consumed by the mining hardware, we have designed the mining hardware to simultaneously run longer and consume much less electricity. We have also compared our techniques with other popular techniques that are already in existence with respect to GPU mining.

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“…Many computers cannot handle the amount of computation required during the mining process. Furthermore, if a network has a limited number of transactions, continuous mining of empty blocks is a waste of energy [6], computation, bandwidth, and storage space. The downloading of the mined empty blocks by all the nodes in the network has a detrimental impact on network bandwidth.…”

Section: Introductionmentioning

confidence: 99%

Smart auto mining (SAM) for industrial IoT blockchain network

et al. 2022

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This work proposes smart auto mining (SAM) for resource-efficient mining in a blockchain network. The SAM algorithm stops the miners when there is zero pending transaction and starts the miner when there is at least one transaction sent into the network. The miner listens to the network to identify when a transaction has been made by a node. The model does not need any instruction to start mining when there is a pending transaction. The results show that a private Ethereum network produced over 300% more blocks in a 12-h period with 599,950 transactions compared to when SAM is applied. The proposed algorithm is also able to reduce the storage used by the chaindata by 14%. The overhead of mining is decreased by reducing the production of empty blocks in the network which saves energy, storage space, network bandwidth and computational complexity.

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Energy and Resource Consumption in Cryptocurrency Mining: A Detailed Comparison

Cited by 4 publications

References 15 publications

A survey of deep learning applications in cryptocurrency

A survey of deep learning applications in cryptocurrency

A Novel Optimization for GPU Mining Using Overclocking and Undervolting

Smart auto mining (SAM) for industrial IoT blockchain network

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