The effect of network topology on credit network throughput

Credit networks rely on decentralized, pairwise trust relationships (channels) to exchange money or goods. arise naturally in many financial systems, including the recent construct of payment channel blockchain systems. An important performance metric for these is their transaction throughput. However, predicting throughput a credit network nontrivial. Unlike traditional communication channels, channels can become imbalanced; they are unable support more transactions given direction once limit has been reached. This potential imbalance creates complex dependency between network’s and its topology, path choices, balances (state) every channel. Even worse, certain combinations factors lead deadlocked states where no make progress. In this paper, we study relationship topology state. We show that presence deadlocks completely characterizes sensitivity different states. Although identifying an arbitrary NP-hard, propose peeling algorithm inspired by decoding algorithms erasure codes upper bounds severity deadlock. use as tool compare topologies well aid synthesis robust deadlocks.