Collaborative Research: CNS Core: Small: Cooperation and Competition in Payment Channel Networks: Routing, Pricing, and Network Formation

比特币和以太坊等基于区块链的加密货币的可扩展性阻碍了它们的广泛采用。这是由于它们的底层共识机制需要大量的资源消耗来保证唯一和同步的全局状态。为了解决这个可伸缩性问题，人们提出了支付通道网络（pcn）来实现即时和廉价的支付，而不需要昂贵和缓慢的区块链交易。然而，PCN的概念仍处于萌芽阶段，对其缺乏基本的认识。该项目的目标是从优化、博弈论和经济角度对pcn进行全面研究，为pcn中的路由、定价和网络形成提供一套先进的算法、理论和机制。这个与科罗拉多矿业学院和亚利桑那州立大学的研究人员合作的项目预计将通过从优化、博弈论和经济角度研究路由、定价和网络形成问题，为pcn奠定算法、理论和经济基础。通过将优化、博弈论和微观经济学的技术结合在一起，该项目将产生以下几个进展：1)对pcn的深刻理解；考虑平衡约束和到期约束的pcn现实模型；基于路径依赖约束的pcn支付路由的高级算法；4)多种支付路径竞争可用余额时的严谨的余额分配分析模型；5)参与者策略行为对pcn路由和pcn形成影响的科学理论；6)新的经济方法，为如何影响pcn的参与者以最低成本成功实现链下支付提供指导。预计该项目将在许多领域产生重大影响：1)研究界：在PCN研究领域开辟新的前沿，在理解PCN方面开辟新的领域；2)经济：加快采用基于区块链的加密货币，从而提高美国的经济竞争力；3)环境：通过鼓励更多的链下交易，减少区块链技术带来的能源消耗和碳足迹；4)教育：通过课程开发、学生发展、K-12外展活动和研究成果的传播，将本研究融入教育；5)社会：通过传播研究成果、与当地公司合作、社区聚会和公开演讲，提高人们对区块链和pcn的认识和兴趣。该项目的成果，包括源代码和数据集，将在项目网站（https://people.mines.edu/djyang/research/project-pcn/）上保存至少五年，并将向公众开放。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The scalability of blockchain-based cryptocurrencies such as Bitcoin and Ethereum hinders their wide adoption. This is due to the massive resource consumption required by their underlying consensus mechanisms for guaranteeing the unique and synchronized global state. To address this scalability issue, Payment Channel Networks (PCNs) have been proposed to enable instant and inexpensive payments without requiring expensive and slow blockchain transactions. However, the concept of PCN is still at its nascent stage, and its fundamental understanding is still lacking. The goal of this project is to conduct a comprehensive study of PCNs from optimization, game theoretic, and economic perspectives, by providing an advanced suite of algorithms, theories, and mechanisms for routing, pricing, and network formation in PCNs. This collaborative project with investigators from Colorado School of Mines and Arizona State University is expected to lay the algorithmic, theoretical, and economic foundation in PCNs by studying routing, pricing, and network formation problems from optimization, game theoretic, and economic perspectives. By weaving together techniques from optimization, game theory, and microeconomics, this project will yield several advances: 1) Insightful understanding about PCNs; 2) Realistic models of PCNs considering both balance constraints and expiry constraints; 3) Advanced algorithms for routing a payment in PCNs subject to path-dependent constraints; 4) Rigorous analytical models of balance allocation when multiple payment paths compete for the available balance; 5) Scientific theories about the impact of the participants' strategic behavior on the routing in PCNs and the formation of PCNs; 6) New economic approaches that provide guidelines on how to influence the participants in PCNs to make off-chain payments successful at the minimum cost.This project is expected to have significant impacts in many sectors: 1) Research community: giving rise to new frontiers in PCN research area and break new ground in the understanding PCNs; 2) Economy: expediting the adoption of blockchain-based cryptocurrencies and thus increase the economic competitiveness of the US; 3) Environment: reducing the energy consumption and carbon footprint caused by blockchain technology by encouraging more off-chain transactions; 4) Education: integrating this research into education through curriculum development, student development, K-12 outreach activities, and dissemination of research results; and 5) Society: raising awareness and interests in the blockchain and PCNs through disseminating the research results, partnerships with local companies, community meetups, and public talks.The outcome of this project, including source codes and dataset, will be maintained at the project website (https://people.mines.edu/djyang/research/project-pcn/) for at least five years, and will be made available to the public.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.