research-article

Games of Miners

Authors:

Pingzhong Tang,

Yulong ZengAuthors Info & Claims

AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems

Pages 1323 - 1331

Published: 13 May 2020 Publication History

Abstract

Conventional wisdom believes cryptocurrency miners should always work on particular token at their full power. In this paper, however, we show that miners' equilibrium strategy deviates from it, which affects the system security and energy-efficiency. Specifically, we model mining as a game where each miner has limited mining power and compete for multiple tokens. We analyze both pure Nash-equilibrium and Stackelberg-equilibrium of this game, deriving their closed-forms. It is suggested that miners might not exert full power, which, compared with fully-powered mining, provides less mining power for a token and thus makes it more vulnerable to attacks, while it helps to reduce energy consumption. Simulation results show that with more disparate capacity, this effect is more significant. Our results also show that miners should disperse power among all compatible tokens instead of only one, which matches realistic statistics well.

References

[1]

Colleen Alkalay-Houlihan and Nisarg Shah. 2019. The Pure Price of Anarchy of Pool Block Withholding Attacks in Bitcoin Mining. In AAAI 2019.

[2]

Eitan Altman, Alexandre Reiffers-Masson, Daniel Sadoc Menasché, Mandar Datar, Swapnil Dhamal, and Corinne Touati. 2018. Mining competition in a multi-cryptocurrency ecosystem at the network edge: A congestion game approach.

[3]

Nick Arnosti and S. Matthew Weinberg. 2018. Bitcoin: A Natural Oligopoly. (2018). arxiv: cs.CR/1811.08572

[4]

George Bissias, Brian N Levine, and David Thibodeau. 2019. Greedy but cautious: Conditions for miner convergence to resource allocation equilibrium. arXiv preprint arXiv:1907.09883 (2019).

[5]

Jonathan Chiu, Thorsten Koeppl, et almbox. 2018. Incentive compatibility on the blockchain. Technical Report. Bank of Canada.

[6]

CoinMarketCap. 2019. Cryptocurrency market capitalizations. (2019). https://coinmarketcap.com/all/views/all/ [Online; accessed Nov-2019].

[7]

Antoine-Augustin Cournot. 1838. Recherches sur les principes mathématiques de la théorie des richesses par Augustin Cournot. chez L. Hachette.

[8]

Nicola Dimitri. 2017. Bitcoin mining as a contest. Ledger, Vol. 2 (2017), 31--37.

[9]

Ittay Eyal. 2015. The miner's dilemma. In 2015 IEEE Symposium on Security and Privacy. IEEE, 89--103.

Digital Library

[10]

Ittay Eyal and Emin Gün Sirer. 2018. Majority is not enough: Bitcoin mining is vulnerable. Commun. ACM, Vol. 61, 7 (2018), 95--102.

Digital Library

[11]

Wenyi Fang, Pingzhong Tang, and Song Zuo. 2016. Digital good exchange. In Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems. 1277--1278.

[12]

Uriel Feige, Ron Lavi, and Moshe Tennenholtz. 2013. Competition among asymmetric sellers with fixed supply. In Proceedings of the fourteenth ACM conference on Electronic commerce. ACM, 415--416.

Digital Library

[13]

Michal Feldman, Kevin Lai, and Li Zhang. 2005. A price-anticipating resource allocation mechanism for distributed shared clusters. In Proceedings of the sixth ACM conference on Electronic commerce. ACM, 127--136.

Digital Library

[14]

Amos Fiat, Anna Karlin, Elias Koutsoupias, and Christos Papadimitriou. 2019. Energy Equilibria in Proof-of-Work Mining. In Proceedings of the 2019 ACM Conference on Economics and Computation. ACM, 489--502.

Digital Library

[15]

Lawrence Friedman. 1958. Game-theory models in the allocation of advertising expenditures. Operations research, Vol. 6, 5 (1958), 699--709.

[16]

Juan Garay, Aggelos Kiayias, and Nikos Leonardos. 2015. The bitcoin backbone protocol: Analysis and applications. In Annual International Conference on the Theory and Applications of Cryptographic Techniques. Springer, 281--310.

[17]

Kurtulucs Gemici, Elias Koutsoupias, Barnabé Monnot, Christos Papadimitriou, and Georgios Piliouras. 2018. Wealth Inequality and the Price of Anarchy. arXiv preprint arXiv:1802.09269 (2018).

[18]

Adem Efe Gencer, Soumya Basu, Ittay Eyal, Robbert Van Renesse, and Emin Gün Sirer. 2018. Decentralization in bitcoin and ethereum networks. arXiv preprint arXiv:1801.03998 (2018).

[19]

Corrado Gini. 1997. Concentration and dependency ratios. Rivista di politica economica, Vol. 87 (1997), 769--792.

[20]

Guy Goren and Alexander Spiegelman. 2019. Mind the Mining. In Proceedings of the 2019 ACM Conference on Economics and Computation. ACM, 475--487.

Digital Library

[21]

Ramesh Johari and John N Tsitsiklis. 2004. Efficiency loss in a network resource allocation game. Mathematics of Operations Research, Vol. 29, 3 (2004), 407--435.

Digital Library

[22]

Frank Kelly. 1997. Charging and rate control for elastic traffic. European transactions on Telecommunications, Vol. 8, 1 (1997), 33--37.

[23]

Olga Kharif. 2018. Bitcoin Cash Clash Is Costing Billions With No End in Sight. (2018). https://www.bloomberg.com/news/articles/2018--11--16/bitcoin-cash-clash-is-costing-billions-with-no-end-in-sight

[24]

Aggelos Kiayias, Elias Koutsoupias, Maria Kyropoulou, and Yiannis Tselekounis. 2016. Blockchain Mining Games. In Proceedings of the 2016 ACM Conference on Economics and Computation (EC '16). ACM, New York, NY, USA, 365--382. https://doi.org/10.1145/2940716.2940773

Digital Library

[25]

Elias Koutsoupias, Philip Lazos, Paolo Serafino, and Foluso Ogunlana. 2019. Blockchain Mining Games with Pay Forward. arXiv preprint arXiv:1905.07397 (2019).

[26]

Elias Koutsoupias and Christos Papadimitriou. 1999. Worst-case equilibria. In Annual Symposium on Theoretical Aspects of Computer Science. Springer, 404--413.

[27]

Yoad Lewenberg, Yoram Bachrach, Yonatan Sompolinsky, Aviv Zohar, and Jeffrey S Rosenschein. 2015. Bitcoin mining pools: A cooperative game theoretic analysis. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. Citeseer, 919--927.

[28]

Ziyao Liu, Nguyen Cong Luong, Wenbo Wang, Dusit Niyato, Ping Wang, Ying-Chang Liang, and Dong In Kim. 2019. A Survey on Applications of Game Theory in Blockchain. arXiv preprint arXiv:1902.10865 (2019).

[29]

Francisco J Marmolejo-Coss'io, Eric Brigham, Benjamin Sela, and Jonathan Katz. 2019. Competing (Semi)-Selfish Miners in Bitcoin. arXiv preprint arXiv:1906.04502 (2019).

[30]

Vahab S Mirrokni, Renato Paes Leme, Pingzhong Tang, and Song Zuo. 2016. Dynamic Auctions with Bank Accounts. In IJCAI, Vol. 16. 387--393.

[31]

Satoshi Nakamoto. 2008. Bitcoin: a peer-to-peer electronic cash system. (2008).

[32]

Martin J Osborne and Carolyn Pitchik. 1986. Price competition in a capacity-constrained duopoly. Journal of Economic Theory, Vol. 38, 2 (1986), 238--260.

[33]

Emiliano Pagnotta. 2018. Bitcoin as Decentralized Money: Prices, Mining Rewards, and Network Security. Mining Rewards, and Network Security (October 26, 2018) (2018).

[34]

Tönu Puu and Manuel Ru'iz Mar'in. 2006. The dynamics of a triopoly Cournot game when the competitors operate under capacity constraints. Chaos, Solitons & Fractals, Vol. 28, 2 (2006), 403--413.

[35]

Tönu Puu and Anna Norin. 2003. Cournot duopoly when the competitors operate under capacity constraints. Chaos, Solitons & Fractals, Vol. 18, 3 (2003), 577--592.

[36]

Weiran Shen and Pingzhong Tang. 2017. Practical versus optimal mechanisms. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. 78--86.

Digital Library

[37]

Weiran Shen, Pingzhong Tang, and Yulong Zeng. 2018a. Buyer-Optimal Distribution. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 1513--1521.

Digital Library

[38]

Weiran Shen, Pingzhong Tang, and Yulong Zeng. 2018b. A closed-form characterization of buyer signaling schemes in monopoly pricing. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 1531--1539.

[39]

Weiran Shen, Pingzhong Tang, and Yulong Zeng. 2019. Buyer Signaling Games in Auctions. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 1591--1599.

[40]

Alexander Spiegelman, Idit Keidar, and Moshe Tennenholtz. 2018. Game of coins. arXiv preprint arXiv:1805.08979 (2018).

[41]

Pingzhong Tang and Zihe Wang. 2017. Optimal mechanisms with simple menus. Journal of Mathematical Economics, Vol. 69 (2017), 54--70.

[42]

Pingzhong Tang, Zihe Wang, and Xiaoquan Zhang. 2016. Optimal commitments in asymmetric auctions with incomplete information. In Proceedings of the 2016 ACM Conference on Economics and Computation. 197--211.

Digital Library

[43]

Pingzhong Tang, Yulong Zeng, and Song Zuo. 2017. Fans Economy and All-Pay Auctions with Proportional Allocations. In AAAI. 713--719.

[44]

Itay Tsabary and Ittay Eyal. 2018. The gap game. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. ACM, 713--728.

Digital Library

[45]

Heinrich Von Stackelberg. 1934. Marktform und gleichgewicht. J. springer.

[46]

Josiah Wilmoth. 2018. Bitmain's Mining Pools Now Control Nearly 51 Percent of the Bitcoin Hashrate. (2018). https://finance.yahoo.com/news/bitmain-mining-pools-now-control-155804143.html

[47]

Yulong Zeng and Song Zuo. 2019. The Matthew Effect in Computation Contests: High Difficulty May Lead to 51% Dominance?. In The World Wide Web Conference. 2281--2289.

Digital Library

Cited By

Chen ZLiu ZZhou Y(2024)Analyzing the blockchain mining strategy in Industrial Internet of ThingsFuture Generation Computer Systems10.1016/j.future.2024.05.003159:C(51-63)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.future.2024.05.003
Birmpas GGan JHollender AMarmolejo-Cossío FRajgopal NVoudouris A(2022)Optimally Deceiving a Learning Leader in Stackelberg GamesJournal of Artificial Intelligence Research10.1613/jair.1.1254272(507-531)Online publication date: 4-Jan-2022
https://dl.acm.org/doi/10.1613/jair.1.12542
Xiao YMarkovich SKuzmanovic AHerlihy MNarula N(2022)Blockchain Mining: Optimal Resource AllocationProceedings of the 4th ACM Conference on Advances in Financial Technologies10.1145/3558535.3559792(294-307)Online publication date: 19-Sep-2022
https://dl.acm.org/doi/10.1145/3558535.3559792

Index Terms

Games of Miners

Recommendations

Moral hazard in games of miners
DAI '19: Proceedings of the First International Conference on Distributed Artificial Intelligence

Cryptocurrency mining, which has attracted substantial attention recently is a game where miners cost mining power and compete for an amount of digital token. In this paper, we revisit this game under new settings that miners' maximal mining powers, ...
A game theoretic analysis of resource mining in blockchain
Abstract
Blockchain and cryptocurrency are a hot topic in today’s digital world. In this paper, we create a game theoretic model in continuous time. We consider a dynamic game model of the bitcoin market, where miners or players use mining systems to mine ...
A Game-Theoretical Analysis of Charging Strategies for Competing Double Auction Marketplaces
Multi-Agent Systems and Agreement Technologies
Abstract
The double auction marketplaces usually charge fees to traders to make profits, but little work has been done on analyzing how marketplaces charge appropriate fees to make profits in multiple marketplaces competing environment. In this paper, we ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems

May 2020

2289 pages

ISBN:9781450375184

General Chairs:
Amal El Fallah Seghrouchni
Sorbonne University, France
,
Gita Sukthankar
University of Central Florida, United States
,
Program Chairs:
Bo An
Nanyang Technological University, Singapore
,
Neil Yorke-Smith Yorke-Smith
Delft University of Technology, Netherlands

Sponsors

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 13 May 2020

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Beijing Academy of Artificial Intelligence
China's Ministry of science and technology
Turing AI Institute of Nanjing

Conference

AAMAS '19

Sponsor:

SIGAI

AAMAS '19: International Conference on Autonomous Agents and Multiagent Systems

May 9 - 13, 2020

Auckland, New Zealand

Acceptance Rates

Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
77
Total Downloads

Downloads (Last 12 months)8
Downloads (Last 6 weeks)0

Reflects downloads up to 21 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Chen ZLiu ZZhou Y(2024)Analyzing the blockchain mining strategy in Industrial Internet of ThingsFuture Generation Computer Systems10.1016/j.future.2024.05.003159:C(51-63)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.future.2024.05.003
Birmpas GGan JHollender AMarmolejo-Cossío FRajgopal NVoudouris A(2022)Optimally Deceiving a Learning Leader in Stackelberg GamesJournal of Artificial Intelligence Research10.1613/jair.1.1254272(507-531)Online publication date: 4-Jan-2022
https://dl.acm.org/doi/10.1613/jair.1.12542
Xiao YMarkovich SKuzmanovic AHerlihy MNarula N(2022)Blockchain Mining: Optimal Resource AllocationProceedings of the 4th ACM Conference on Advances in Financial Technologies10.1145/3558535.3559792(294-307)Online publication date: 19-Sep-2022
https://dl.acm.org/doi/10.1145/3558535.3559792
Birmpas GGan JHollender AMarmolejo-Cossío FRajgopal NVoudouris ALarochelle HRanzato MHadsell RBalcan MLin H(2020)Optimally deceiving a learning leader in stackelberg gamesProceedings of the 34th International Conference on Neural Information Processing Systems10.5555/3495724.3497456(20624-20635)Online publication date: 6-Dec-2020
https://dl.acm.org/doi/10.5555/3495724.3497456

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents