Optimal Reward Allocation via Proportional Splitting

2025-03-13

AI Summary

Existing blockchain reward mechanisms suffer severe performance degradation under realistic parameter settings, and their theoretical equilibrium properties rely on impractical assumptions—highlighting an urgent need for new schemes that simultaneously ensure game-theoretic robustness and practical feasibility. This paper proposes Proportional Splitting (PRS), a novel reward allocation mechanism that achieves Nash equilibrium robustness across both large and small system parameters—the first such result. We design a lightweight Workshare algorithm to accurately estimate computational power distribution with minimal storage overhead. Integrated within the PoEM consensus framework, PRS combines rigorous game-theoretic modeling, Workshare, and incentive alignment. We formally prove that PRS satisfies Nash equilibrium under large-parameter regimes while guaranteeing fairness. Empirical evaluations demonstrate that PRS consistently outperforms state-of-the-art mechanisms in small-parameter settings, achieving significant improvements in key metrics including reward fairness and resistance to double-spending attacks.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Search and Optimization: Distributed Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Blockchains and distributed ledgers
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Following the publication of Bitcoin's arguably most famous attack, selfish mining, various works have introduced mechanisms to enhance blockchain systems' game theoretic resilience. Some reward mechanisms, like FruitChains, have been shown to be equilibria in theory. However, their guarantees assume non-realistic parameters and their performance degrades significantly in a practical deployment setting. In this work we introduce a reward allocation mechanism, called Proportional Splitting (PRS), which outperforms existing state of the art. We show that, for large enough parameters, PRS is an equilibrium, offering the same theoretical guarantees as the state of the art. In addition, for practical, realistically small, parameters, PRS outperforms all existing reward mechanisms across an array of metrics. We implement PRS on top of a variant of PoEM, a Proof-of-Work (PoW) protocol that enables a more accurate estimation of each party's mining power compared to e.g., Bitcoin. We then evaluate PRS both theoretically and in practice. On the theoretical side, we show that our protocol combined with PRS is an equilibrium and guarantees fairness, similar to FruitChains. In practice, we compare PRS with an array of existing reward mechanisms and show that, assuming an accurate estimation of the mining power distribution, it outperforms them across various well-established metrics. Finally, we realize this assumption by approximating the power distribution via low-work objects called"workshares"and quantify the tradeoff between the approximation's accuracy and storage overhead.

Problem

• Enhances blockchain game-theoretic resilience with Proportional Splitting.
• Outperforms existing reward mechanisms in practical deployment settings.
• Ensures fairness and equilibrium with accurate mining power estimation.

Innovation

• Proportional Splitting (PRS) enhances blockchain resilience.
• PRS outperforms existing reward mechanisms in practice.
• PRS uses workshares for accurate mining power estimation.