maxREE: Maximizing Flow by Replacing Exhausted Edges in Lightning Network
Neeraj Sharma, Kalpesh Kapoor · IEEE Transactions on Network Science and Engineering · 2024
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 themaxREEalgorithm, 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, calledDRLNsim, 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.