Abstract
Payment channel networks like Bitcoin’s Lightning network are an auspicious approach for realizing high transaction throughput and almost-instant confirmations in blockchain networks. However, the ability to successfully conduct payments in such networks relies on the willingness of participants to lock collateral in the network. In Lightning, the key financial incentive to lock collateral are low fees for routing payments of other participants. While users can choose these fees, real-world data indicates that they mainly stick to default fees. By providing insights on beneficial choices for fees, we aim to incentivize users to lock more collateral and improve the effectiveness of the network.
In this paper, we consider a node \(\mathbf {A}\) that given the network topology and the channel details establishes channels and chooses fees to maximize its financial gain. Our contributions are i) formalization of the optimization problem, ii) proving that the problem is NP-hard, and iii) designing and evaluating a greedy algorithm to approximate the optimal solution. In each step, our greedy algorithm establishes a channel that maximizes the increase to \(\mathbf {A}\)’s total reward, which corresponds to maximizing the number of shortest paths passing through \(\mathbf {A}\). Our simulation study leveraged real-world data sets to quantify the impact of our gain optimization and indicates that our strategy is at least a factor two better than other strategies.
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Notes
- 1.
\((|V|-1)(|V|-2)\) is the number of pairs of nodes when not including \(\mathbf {A}\).
- 2.
For the rest of section, we drop the transaction amount tx from the channel fee formula \(\mathbf {f}(Ch_i)\) as it is fixed.
- 3.
- 4.
- 5.
The default fee values may change regarding the imported implementation. Our analysis on dataset shows that 33177 out of 68733 edges use the defaults we adopted.
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Acknowledgments
This work was partially supported by Ripple’s University Blockchain Research Initiative.
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Appendices
A Illustrative Example of the EBC vs. Fee Relationship of a Channel
Illustrative example of the EBC vs. fee relationship of a channel.
B Pseudocode Channel Fee Function
Algorithm 2 is a recursive algorithm for determining the best fee in one step of the greedy algorithm.
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Ersoy, O., Roos, S., Erkin, Z. (2020). How to Profit from Payments Channels. In: Bonneau, J., Heninger, N. (eds) Financial Cryptography and Data Security. FC 2020. Lecture Notes in Computer Science(), vol 12059. Springer, Cham. https://doi.org/10.1007/978-3-030-51280-4_16
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