Online Admission Control and Rebalancing in Payment Channel Networks

Mahsa Bastankhah; Krishnendu Chatterjee; Mohammad Ali Maddah-Ali; Stefan Schmid; Jakub Svoboda; Michelle Yeo

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arXiv · 2209.11936

Online Admission Control and Rebalancing in Payment Channel Networks

Mahsa Bastankhah·Krishnendu Chatterjee·Mohammad Ali Maddah-Ali·Stefan Schmid·Jakub Svoboda·Michelle Yeo

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Abstract

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.

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Mahsa Bastankhah, Krishnendu Chatterjee, Mohammad Ali Maddah-Ali, Stefan Schmid, Jakub Svoboda, Michelle Yeo. 2022-09-24. Online Admission Control and Rebalancing in Payment Channel Networks. https://arxiv.org/abs/2209.11936

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