maxREE: Maximizing Flow by Replacing Exhausted Edges in Lightning Network

Blockchain-based cryptocurrencies have grown rapidly over the past decade, but issues with scalability are limiting their wider adoption. Payment Channel Network, a layer two solution, is an alternative for enhancing the scalability of a blockchain network. Two users can engage in some off-chain transactions via payment channels in the network they build in order to avoid the time and expense of on-chain settlement. The number of nodes in the Bitcoin payment channel network has nearly doubled over the last two years, and this network size is proliferating. The number of transactions on the network will increase along with its growth. However, the existing distributed routing algorithms cannot effectively schedule several concurrent transactions due to their static nature. We propose the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">maxREE</i> algorithm, which efficiently handles concurrent transactions with negligible overhead. Our algorithm considers substituting the necessary edges with superior alternatives to prevent the saturation of a channel's directional capacity while maintaining the height of the underlying routing tree. The transaction flow was enhanced by our proposed algorithm's self-rebalancing and link load sharing. Without compromising network privacy, the unused links are dynamically substituted for the congested ones. We have also developed a simulator, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DRLNsim</i>, to compare our algorithm with existing techniques. On the simulator, the routing approaches are examined using multiple custom network sizes. The proposed method enabled concurrent transactions 58% more effectively on average than existing techniques. The simulation's outcomes mirror the patterns found through theoretical study.

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Publication Details

Journal
IEEE Transactions on Network Science and Engineering
Published
2024-12-25
DOI
https://doi.org/10.1109/tnse.2024.3522198
Citations
3
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.75
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article

maxREE: Maximizing Flow by Replacing Exhausted Edges in Lightning Network

Kalpesh Kapoor, Neeraj Sharma
3 citations
IEEE Transactions on Network Science and Engineering
Data Visualization and Analytics
0.75
article

maxREE: Maximizing Flow by Replacing Exhausted Edges in Lightning Network

Kalpesh Kapoor, Neeraj Sharma
article en
3 citations

Abstract

Blockchain-based cryptocurrencies have grown rapidly over the past decade, but issues with scalability are limiting their wider adoption. Payment Channel Network, a layer two solution, is an alternative for enhancing the scalability of a blockchain network. Two users can engage in some off-chain transactions via payment channels in the network they build in order to avoid the time and expense of on-chain settlement. The number of nodes in the Bitcoin payment channel network has nearly doubled over the last two years, and this network size is proliferating. The number of transactions on the network will increase along with its growth. However, the existing distributed routing algorithms cannot effectively schedule several concurrent transactions due to their static nature. We propose the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">maxREE</i> algorithm, which efficiently handles concurrent transactions with negligible overhead. Our algorithm considers substituting the necessary edges with superior alternatives to prevent the saturation of a channel's directional capacity while maintaining the height of the underlying routing tree. The transaction flow was enhanced by our proposed algorithm's self-rebalancing and link load sharing. Without compromising network privacy, the unused links are dynamically substituted for the congested ones. We have also developed a simulator, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DRLNsim</i>, to compare our algorithm with existing techniques. On the simulator, the routing approaches are examined using multiple custom network sizes. The proposed method enabled concurrent transactions 58% more effectively on average than existing techniques. The simulation's outcomes mirror the patterns found through theoretical study.

IEEE Transactions on Network Science and EngineeringVol. 12(2)
Indian Institute of Technology Guwahati (IN)
Climate action
Openalex Percentile: Top 26%
Data Visualization and Analytics
0.75
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