论文标题
在线录取控制和付款渠道网络中的重新平衡
Online Admission Control and Rebalancing in Payment Channel Networks
论文作者
论文摘要
支付渠道网络(PCN)是提高加密货币可扩展性的有前途技术。但是,PCN面临的挑战是,某些路线的频繁使用可能会沿一个方向耗尽通道,从而阻止进一步的交易。为了收获PCN的全部潜力,需要充电和重新平衡的机制来提供渠道,以及入学控制逻辑,以确定在能力不足的情况下拒绝哪些交易。本文提出了此优化问题的正式模型。特别是,我们考虑了一种在线算法的观点,即交易以不可预测的方式随着时间的流逝而到达。我们的主要贡献是竞争性的在线算法,随着时间的流逝,可证明保证。我们从经验上评估了随机生成的交易的算法,以将算法的平均性能与我们的理论界限进行比较。我们还展示了该模型和方法与经典通信网络中相关问题的不同。
Payment channel networks (PCNs) are a promising technology to improve the scalability of cryptocurrencies. PCNs, however, face the challenge that the frequent usage of certain routes may deplete channels in one direction, and hence prevent further transactions. In order to reap the full potential of PCNs, recharging and rebalancing mechanisms are required to provision channels, as well as an admission control logic to decide which transactions to reject in case capacity is insufficient. This paper presents a formal model of this optimisation problem. In particular, we consider an online algorithms perspective, where transactions arrive over time in an unpredictable manner. Our main contributions are competitive online algorithms which come with provable guarantees over time. We empirically evaluate our algorithms on randomly generated transactions to compare the average performance of our algorithms to our theoretical bounds. We also show how this model and approach differs from related problems in classic communication networks.