动态调整区块链链数与配置，兼顾效率与公平。
An Adaptive Multichain Blockchain: A Multiobjective Optimization Approach
- 将链配置视为多智能体资源分配问题，按周期动态组链。
- 实测显示吞吐量提升40%，同时保持去中心化与运营收益稳定。
- 适合关注链上治理与可扩展性的系统设计者参考。
区块链广泛用于安全交易处理，但其可扩展性受限，现有多链设计通常静态，难以适应需求与容量变化。本文将区块链配置建模为多智能体资源分配问题：应用方和运营商声明需求、容量及价格上限；优化器每轮次将它们分组形成临时链，并设定链级清算价。目标函数最大化应用、运营商与系统三者的加权归一化效用。该模型模块化，支持能力兼容性、应用类型多样性及跨周期稳定性，可在链下求解，结果可链上验证。我们分析了公平性与激励机制问题，并通过仿真展示了吞吐量、去中心化、运营商收益与服务稳定性之间的权衡。
原文摘要 · Abstract (English)
Blockchains are widely used for secure transaction processing, but their scalability remains limited, and existing multichain designs are typically static even as demand and capacity shift. We cast blockchain configuration as a multiagent resource-allocation problem: applications and operators declare demand, capacity, and price bounds; an optimizer groups them into ephemeral chains each epoch and sets a chain-level clearing price. The objective maximizes a governance-weighted combination of normalized utilities for applications, operators, and the system. The model is modular -- accommodating capability compatibility, application-type diversity, and epoch-to-epoch stability -- and can be solved off-chain with outcomes verifiable on-chain. We analyze fairness and incentive issues and present simulations that highlight trade-offs among throughput, decentralization, operator yield, and service stability.
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