网络拓扑结构对信用网络吞吐量的影响
The Effect of Network Topology on Credit Network Throughput
摘要：
信用网络依赖于分散的、成对的信任关系（渠道）来交换货币或商品。信用网络在许多金融系统中自然出现，包括最近在区块链系统中构建的支付通道网络。这些网络的一个重要性能指标是它们的事务吞吐量。然而，预测信用网络的吞吐量是不平凡的。与传统的通信渠道不同，信贷渠道可能变得不平衡;一旦达到信贷限额，它们就无法支持给定方向的更多交易。这种潜在的不平衡在网络的吞吐量与其拓扑结构、路径选择和每个通道上的信用余额（状态）之间产生了复杂的依赖关系。更糟糕的是，这些因素的某些组合可能导致信用网络陷入僵局，没有交易可以取得进展。本文研究了信用网络的吞吐量与其拓扑结构和信用状态之间的关系。我们表明，死锁的存在完全表征了网络的吞吐量对不同信用状态的敏感性。尽管我们表明识别任意拓扑中的死锁是NP难的，但我们提出了一种受擦除码解码算法启发的剥离算法，该算法限制了死锁的严重程度。我们使用的剥离算法作为一种工具，比较不同的拓扑结构的性能，以及援助的合成拓扑结构的鲁棒性死锁。
英文摘要：
Credit networks rely on decentralized, pairwise trust relationships (channels) to exchange money or goods. Credit networks arise naturally in many financial systems, including the recent construct of payment channel networks in blockchain systems. An important performance metric for these networks is their transaction throughput. However, predicting the throughput of a credit network is nontrivial. Unlike traditional communication channels, credit channels can become imbalanced; they are unable to support more transactions in a given direction once the credit limit has been reached. This potential for imbalance creates a complex dependency between a network's throughput and its topology, path choices, and the credit balances (state) on every channel. Even worse, certain combinations of these factors can lead the credit network to deadlocked states where no transactions can make progress. In this paper, we study the relationship between the throughput of a credit network and its topology and credit state. We show that the presence of deadlocks completely characterizes a network's throughput sensitivity to different credit states. Although we show that identifying deadlocks in an arbitrary topology is NP-hard, we propose a peeling algorithm inspired by decoding algorithms for erasure codes that upper bounds the severity of the deadlock. We use the peeling algorithm as a tool to compare the performance of different topologies as well as to aid in the synthesis of topologies robust to deadlocks.
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