Distributionally Robust Game for Proof-of-Work Blockchain Mining Under Resource Uncertainties
Xunqiang Lan, Xiao Tang, Ruonan Zhang, Bin Li, Qinghe Du, Dusit Niyato, and Zhu Han

TL;DR
This paper models blockchain proof-of-work mining as a distributionally robust game accounting for resource uncertainties, proposing equilibrium solutions and algorithms to enhance robustness and performance in diverse mining environments.
Contribution
It introduces a novel distributionally robust game framework for PoW mining under resource uncertainties, with equilibrium analysis and algorithms for robust strategy optimization.
Findings
The equilibrium existence is proven for the robust mining game.
Proposed algorithms effectively converge to the equilibrium.
Approaches improve robustness against resource uncertainties in blockchain mining.
Abstract
Blockchain plays a crucial role in ensuring the security and integrity of decentralized systems, with the proof-of-work (PoW) mechanism being fundamental for achieving distributed consensus. As PoW blockchains see broader adoption, an increasingly diverse set of miners with varying computing capabilities participate in the network. In this paper, we consider the PoW blockchain mining, where the miners are associated with resource uncertainties. To characterize the uncertainty computing resources at different mining participants, we establish an ambiguous set representing uncertainty of resource distributions. Then, the networked mining is formulated as a non-cooperative game, where distributionally robust performance is calculated for each individual miner to tackle the resource uncertainties. We prove the existence of the equilibrium of the distributionally robust mining game. To…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Mobile Crowdsensing and Crowdsourcing · Big Data and Digital Economy
