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<p>The blockchain trilemma, which is the inherent tension among scalability, security, and decentralization, remains a fundamental obstacle to distributed system adoption. While Arweave’s permanent storage protocol offers a promising foundation, its behavior under dynamic loads and large-scale adversarial conditions lacks rigorous characterization. This work enhances and empirically validates Arweave’s Proof-of-Access (PoA) consensus by augmenting it with a Lyapunov-stable dynamic block sizing mechanism and a Verifiable Delay Function (VDF) for enhanced randomness, while providing the first large-scale analysis of its behavior under adversarial conditions. We prove that the pending transaction queue remains bounded under stochastic arrivals, guaranteeing predictable latency even during flash crowds. Through large-scale simulations scaling to 10,000+ nodes, we demonstrate that PoA maintains a chain quality of 0.83 under 40% Byzantine adversaries: outperforming Bitcoin-NG and Omniledger while achieving Visa-level throughput (162–7,200 TPS) on commodity $300 hardware. Our analysis further quantifies storage efficiency (3,426<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\times \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>×</mo> </math></EquationSource> </InlineEquation> reduction versus Bitcoin), computational scalability (R² = 0.98 linear CPU scaling), and storage distribution equity (Gini coefficient &lt;0.2 at 50,000 nodes). The framework’s capacity to sustain sub-second confirmation time (1.15 s for 200 MB blocks note that this is inclusion time, not irreversible finality, which requires &#xa0;8.3&#xa0;h), Sybil resistance, and Tier-S decentralization (Nakamoto Coefficient &gt;100) positions it as a foundational infrastructure for IoT, healthcare, and decentralized finance. We conclude by outlining a roadmap integrating deep reinforcement learning for autonomous parameter tuning, while acknowledging that the trilemma is mitigated rather than fully resolved. All results are obtained from large-scale simulations; real-world validation has not yet been performed.</p>

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Formal validation of proof-of-access architectures for mitigating the blockchain trilemma

  • 期刊论文

  • 发表日期：

    2026年5月20日

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  • Saha Reno,
  • Koushik Roy,
  • Khandakar Md. Shafin

摘要

The blockchain trilemma, which is the inherent tension among scalability, security, and decentralization, remains a fundamental obstacle to distributed system adoption. While Arweave’s permanent storage protocol offers a promising foundation, its behavior under dynamic loads and large-scale adversarial conditions lacks rigorous characterization. This work enhances and empirically validates Arweave’s Proof-of-Access (PoA) consensus by augmenting it with a Lyapunov-stable dynamic block sizing mechanism and a Verifiable Delay Function (VDF) for enhanced randomness, while providing the first large-scale analysis of its behavior under adversarial conditions. We prove that the pending transaction queue remains bounded under stochastic arrivals, guaranteeing predictable latency even during flash crowds. Through large-scale simulations scaling to 10,000+ nodes, we demonstrate that PoA maintains a chain quality of 0.83 under 40% Byzantine adversaries: outperforming Bitcoin-NG and Omniledger while achieving Visa-level throughput (162–7,200 TPS) on commodity $300 hardware. Our analysis further quantifies storage efficiency (3,426 \(\times \) × reduction versus Bitcoin), computational scalability (R² = 0.98 linear CPU scaling), and storage distribution equity (Gini coefficient <0.2 at 50,000 nodes). The framework’s capacity to sustain sub-second confirmation time (1.15 s for 200 MB blocks note that this is inclusion time, not irreversible finality, which requires  8.3 h), Sybil resistance, and Tier-S decentralization (Nakamoto Coefficient >100) positions it as a foundational infrastructure for IoT, healthcare, and decentralized finance. We conclude by outlining a roadmap integrating deep reinforcement learning for autonomous parameter tuning, while acknowledging that the trilemma is mitigated rather than fully resolved. All results are obtained from large-scale simulations; real-world validation has not yet been performed.