Toward Sustainable Blockchain- Exploring Eco Friendly Cryptocurrency Puzzle Generation Using Edge Computing

Blockchain technology has revolutionized various industries, but the energy-intensive nature of cryptocurrency mining, particularly with traditional Proof-Of-Work (PoW) mechanisms, has raised concerns about its environmental sustainability. Traditional proof-of-work (PoW) consensus mechanisms, while effective, have raised significant environmental concerns due to their energy-intensive nature. Hence a comprehensive analysis of eco-friendly cryptocurrency puzzle generation techniques is the need of the hour to potentially mitigate carbon footprint in blockchain networks. The paper investigates the feasibility of reducing the carbon footprint and introducing eco-friendly puzzle generation techniques that can be used with cryptocurrency mining by exploring the potential benefits of integrating Edge computing architecture. Through empirical evaluation, case studies, and outlook, it offers valuable insights for researchers, developers, and policymakers seeking to address the environmental challenges associated with cryptocurrency mining. This paper proposes potential solutions with plausible benefits when adopted by miners through mitigation of the environmental impact of blockchain technology.

Authors

Institutions

Publication Details

Published
2025-03-06
DOI
https://doi.org/10.1109/iatmsi64286.2025.10984490
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Toward Sustainable Blockchain- Exploring Eco Friendly Cryptocurrency Puzzle Generation Using Edge Computing

Suresh Shanmugasundaram, Divya Preya Chidambaram, Kumaravel Chidamparam
Blockchain Technology Applications and Security
article

Toward Sustainable Blockchain- Exploring Eco Friendly Cryptocurrency Puzzle Generation Using Edge Computing

Suresh Shanmugasundaram, Divya Preya Chidambaram, Kumaravel Chidamparam
article en

Abstract

Blockchain technology has revolutionized various industries, but the energy-intensive nature of cryptocurrency mining, particularly with traditional Proof-Of-Work (PoW) mechanisms, has raised concerns about its environmental sustainability. Traditional proof-of-work (PoW) consensus mechanisms, while effective, have raised significant environmental concerns due to their energy-intensive nature. Hence a comprehensive analysis of eco-friendly cryptocurrency puzzle generation techniques is the need of the hour to potentially mitigate carbon footprint in blockchain networks. The paper investigates the feasibility of reducing the carbon footprint and introducing eco-friendly puzzle generation techniques that can be used with cryptocurrency mining by exploring the potential benefits of integrating Edge computing architecture. Through empirical evaluation, case studies, and outlook, it offers valuable insights for researchers, developers, and policymakers seeking to address the environmental challenges associated with cryptocurrency mining. This paper proposes potential solutions with plausible benefits when adopted by miners through mitigation of the environmental impact of blockchain technology.

Sugen Life Sciences (India) (IN), University of Wales Trinity Saint David (GB)
Responsible consumption and production
Openalex Percentile: Top 86%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Toward Sustainable Blockchain- Exploring Eco Friendly Cryptocurrency Puzzle Generation Using Edge Computing — Suresh Shanmugasundaram, Divya Preya Chidambaram, et al. · (2025) | TGRS Research Map | TGRS