Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism

Hao Zeng; Man Li; Helei Cui; Yuefeng Du; Zhiwen Yu; Bin Guo

doi:10.1109/ICDCS57875.2023.00130

Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism

Hao Zeng
, Man Li
, Helei Cui^*
, Yuefeng Du
, Zhiwen Yu
, Bin Guo

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

An increasing number of energy-recycling consensus mechanisms are being employed to address the drawback of proof of work (PoW) wasting computation and energy. For instance, the computing power wasted in solving difficult but meaningless PoW puzzles is used to conduct practical federated learning tasks and train deep learning models. However, there remains a neglected issue of task difficulty adjustment. To address this problem, we propose a method for measuring task difficulty and an algorithm for adjustment to achieve controlled minting and stable transaction processing capacity for cryptocurrency based on energy-recycling consensus mechanisms. Our research evaluates the effectiveness of this algorithm and highlights the potential benefits of this approach. © 2023 IEEE.

Original language	English
Title of host publication	Proceedings - 2023 IEEE 43^rd International Conference on Distributed Computing Systems
Subtitle of host publication	ICDCS 2023
Publisher	IEEE
Pages	1069-1070
ISBN (Electronic)	9798350339864
ISBN (Print)	979-8-3503-3987-1
DOIs	https://doi.org/10.1109/ICDCS57875.2023.00130
Publication status	Published - 2023
Event	43rd IEEE International Conference on Distributed Computing Systems (ICDCS 2023) - Sheraton Hong Kong & Towers, Hong Kong, China Duration: 18 Jul 2023 → 21 Jul 2023 https://icdcs2023.icdcs.org/ https://ieeexplore.ieee.org/xpl/conhome/1000213/all-proceedings

Publication series

Name	Proceedings - International Conference on Distributed Computing Systems
ISSN (Print)	1063-6927
ISSN (Electronic)	2575-8411

Conference

Conference	43rd IEEE International Conference on Distributed Computing Systems (ICDCS 2023)
Place	Hong Kong, China
Period	18/07/23 → 21/07/23
Internet address	https://icdcs2023.icdcs.org/ https://ieeexplore.ieee.org/xpl/conhome/1000213/all-proceedings

Research Keywords

blockchain
consensus mechanism
federated learning
proof of learning

Access Output

10.1109/ICDCS57875.2023.00130

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Cite this

Zeng, H., Li, M., Cui, H., Du, Y., Yu, Z., & Guo, B. (2023). Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism. In Proceedings - 2023 IEEE 43^rd International Conference on Distributed Computing Systems: ICDCS 2023 (pp. 1069-1070). (Proceedings - International Conference on Distributed Computing Systems). IEEE. https://doi.org/10.1109/ICDCS57875.2023.00130

@inproceedings{d99f07ac0ea64c93b1687037baa58b70,

title = "Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism",

abstract = "An increasing number of energy-recycling consensus mechanisms are being employed to address the drawback of proof of work (PoW) wasting computation and energy. For instance, the computing power wasted in solving difficult but meaningless PoW puzzles is used to conduct practical federated learning tasks and train deep learning models. However, there remains a neglected issue of task difficulty adjustment. To address this problem, we propose a method for measuring task difficulty and an algorithm for adjustment to achieve controlled minting and stable transaction processing capacity for cryptocurrency based on energy-recycling consensus mechanisms. Our research evaluates the effectiveness of this algorithm and highlights the potential benefits of this approach. {\textcopyright} 2023 IEEE.",

keywords = "blockchain, consensus mechanism, federated learning, proof of learning",

author = "Hao Zeng and Man Li and Helei Cui and Yuefeng Du and Zhiwen Yu and Bin Guo",

year = "2023",

doi = "10.1109/ICDCS57875.2023.00130",

language = "English",

isbn = "979-8-3503-3987-1",

series = "Proceedings - International Conference on Distributed Computing Systems",

publisher = "IEEE",

pages = "1069--1070",

booktitle = "Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems",

address = "United States",

note = "43rd IEEE International Conference on Distributed Computing Systems (ICDCS 2023) ; Conference date: 18-07-2023 Through 21-07-2023",

url = "https://icdcs2023.icdcs.org/, https://ieeexplore.ieee.org/xpl/conhome/1000213/all-proceedings",

}

Zeng, H, Li, M, Cui, H, Du, Y, Yu, Z & Guo, B 2023, Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism. in Proceedings - 2023 IEEE 43^rd International Conference on Distributed Computing Systems: ICDCS 2023. Proceedings - International Conference on Distributed Computing Systems, IEEE, pp. 1069-1070, 43rd IEEE International Conference on Distributed Computing Systems (ICDCS 2023), Hong Kong, China, 18/07/23. https://doi.org/10.1109/ICDCS57875.2023.00130

Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism. / Zeng, Hao; Li, Man; Cui, Helei et al.
Proceedings - 2023 IEEE 43^rd International Conference on Distributed Computing Systems: ICDCS 2023. IEEE, 2023. p. 1069-1070 (Proceedings - International Conference on Distributed Computing Systems).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Poster

T2 - 43rd IEEE International Conference on Distributed Computing Systems (ICDCS 2023)

AU - Zeng, Hao

AU - Li, Man

AU - Cui, Helei

AU - Du, Yuefeng

AU - Yu, Zhiwen

AU - Guo, Bin

PY - 2023

Y1 - 2023

N2 - An increasing number of energy-recycling consensus mechanisms are being employed to address the drawback of proof of work (PoW) wasting computation and energy. For instance, the computing power wasted in solving difficult but meaningless PoW puzzles is used to conduct practical federated learning tasks and train deep learning models. However, there remains a neglected issue of task difficulty adjustment. To address this problem, we propose a method for measuring task difficulty and an algorithm for adjustment to achieve controlled minting and stable transaction processing capacity for cryptocurrency based on energy-recycling consensus mechanisms. Our research evaluates the effectiveness of this algorithm and highlights the potential benefits of this approach. © 2023 IEEE.

AB - An increasing number of energy-recycling consensus mechanisms are being employed to address the drawback of proof of work (PoW) wasting computation and energy. For instance, the computing power wasted in solving difficult but meaningless PoW puzzles is used to conduct practical federated learning tasks and train deep learning models. However, there remains a neglected issue of task difficulty adjustment. To address this problem, we propose a method for measuring task difficulty and an algorithm for adjustment to achieve controlled minting and stable transaction processing capacity for cryptocurrency based on energy-recycling consensus mechanisms. Our research evaluates the effectiveness of this algorithm and highlights the potential benefits of this approach. © 2023 IEEE.

KW - blockchain

KW - consensus mechanism

KW - federated learning

KW - proof of learning

UR - https://www.scopus.com/pages/publications/85175097649

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85175097649&origin=recordpage

U2 - 10.1109/ICDCS57875.2023.00130

DO - 10.1109/ICDCS57875.2023.00130

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 979-8-3503-3987-1

T3 - Proceedings - International Conference on Distributed Computing Systems

SP - 1069

EP - 1070

BT - Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems

PB - IEEE

Y2 - 18 July 2023 through 21 July 2023

ER -

Zeng H, Li M, Cui H, Du Y, Yu Z, Guo B. Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism. In Proceedings - 2023 IEEE 43^rd International Conference on Distributed Computing Systems: ICDCS 2023. IEEE. 2023. p. 1069-1070. (Proceedings - International Conference on Distributed Computing Systems). Epub 2023 Oct 11. doi: 10.1109/ICDCS57875.2023.00130

Poster: Task Difficulty Adjustment in the Energy-Recycling Consensus Mechanism

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