Reducing Resource and Energy Consumption in Cryptocurrency Mining by using both Proof-of-Stake Algorithm and Renewable Energy

Gundaboina, Lokesh; Badotra, Sumit; Tanwar, Sarvesh; Manik,

doi:10.1109/mecon53876.2022.9752365

Cited by 16 publications

(1 citation statement)

References 11 publications

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“…The architecture for routing is constructed by the sensing nodes that must convey data to the base station, not previously. In MANETs, the most used reactive routing method is AODV [34], whereas in WSN push diffusion [35], in FRA [36] and LRDE [37] are the most prevalent. These techniques save resources during times of inactivity but incur the cost of identifying pathways for each originating node.…”

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confidence: 99%

Intelligent Water Drops Algorithm-Based Aggregation in Heterogeneous Wireless Sensor Network

et al. 2022

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This paper provides a novel implementation of the intelligent water drops (IWD) method for resolving data aggregation issues in heterogeneous wireless sensor networks (WSN). When the aggregating node is utilized to transmit the data to the base station, the research attempts to show that the traffic situations of WSN may be modified appropriately by parameter tuning and algorithm modification. IWD is used to generate an optimum data aggregation tree in WSN as one of its applications. IWD assumes that all nodes in the environment are identical, resulting in identical parameter updates for all nodes. In practical scenarios, however, diverse nodes with variable beginning energy, communication range, and sensing range characteristics are deployed. In order to replicate the influence of heterogeneity in the environment, improved IID (IIWD) is offered as an enhancement to the original IID. The suggested enhancement is appropriate for scenarios in which the aggregation node is utilized to transmit data to the base station in heterogeneous configurations. In terms of residual energy, dead nodes, payload, and network lifespan, a series of simulation results demonstrates that the proposed IIWD significantly improves the accuracy and effectiveness of the IWD method in comparison.

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confidence: 99%

Intelligent Water Drops Algorithm-Based Aggregation in Heterogeneous Wireless Sensor Network

et al. 2022

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A Review on Blockchain Smart Contract Applications

Tanwar,

Gupta,

Tomar

et al. 2023

Lecture Notes in Networks and Systems

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Are cleaner energy and financial technologies needed? Contagion and causality evidence between global fintech markets, energy consumption, and environmental pollution

Ersin,

Bildirici

2024

Clean Techn Environ Policy

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Financial technology (FinTech) depends on high amounts of energy with an upward trend, possibly affecting emissions due to energy consumption (EC). The study investigates tail dependence, contagion, and nonlinear between FinTech, EC, and carbon dioxide emissions (CO2e) with MS-GARCH-copula and MS-GARCH-copula-causality with a daily sample covering 02 Jan 2012–28 December 2022. The method is a generalized version of single-regime GARCH-copula and causality tests to Markov-switching. Empirical results indicated that FinTech, EC, and CO2e series follow nonlinear processes in addition to unit roots as determined by BDS nonlinearity tests and a set of linear and nonlinear unit root tests. Further, for all series, heteroskedasticity and nonlinear forms of heteroskedasticity cannot be rejected by ARCH–LM and White heteroskedasticity tests, leading to the estimation of the series and their joint dynamics by MS-GARCH-copula and a new MS-GARCH-copula based nonlinear Granger-causality test, the RSGCC test, under two distinct regimes characterized with the low and high volatility for extreme tails of data. Positivity and significance of copula parameters under both regimes indicate a high degree of positive but asymmetric tail dependence and contagion between FinTech & EC, in addition to contagion between FinTech & CO2e and EC & CO2e. RSGCC results determine unidirectional causalities from EC to CO2e and from FinTech to CO2e, coupled with bidirectional causality between FinTech and EC, which enhance the dynamics due to feedback effects. The findings of this paper are of importance for two central Sustainable Development Goals. Results could also be used to bring the FinTech markets and EC to the attention of policymakers, researchers, and eco-friendliness-focused portfolio managers. Graphical Abstract

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Reducing Resource and Energy Consumption in Cryptocurrency Mining by using both Proof-of-Stake Algorithm and Renewable Energy

Cited by 16 publications

References 11 publications

Intelligent Water Drops Algorithm-Based Aggregation in Heterogeneous Wireless Sensor Network

Intelligent Water Drops Algorithm-Based Aggregation in Heterogeneous Wireless Sensor Network

A Review on Blockchain Smart Contract Applications

Are cleaner energy and financial technologies needed? Contagion and causality evidence between global fintech markets, energy consumption, and environmental pollution

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