Decentralizing the lightning network: a score-based recommendation strategy for the autopilot system

Abstract

Abstract The fundamental objective of the Lightning Network is to establish a decentralized platform for scaling the Bitcoin network and facilitating high-throughput micropayments. However, this network has gradually deviated from its decentralized topology since its operational inception, and its resources have quickly shifted towards centralization. The evolution of the network and the changes in its topology have been critically reviewed and criticized due to its increasing centralization. This study delves into the network’s topology and the reasons behind its centralized evolution. We explain the incentives of various participating nodes in the network and propose a score-based strategy for the Lightning Autopilot system, which is responsible for automatically establishing new payment channels for the nodes joining the network. Our study demonstrates that utilizing the proposed strategy could significantly aid in reducing the network’s centralization. This strategy is grounded in qualitative labeling of network nodes based on topological and protocol features, followed by the creation of a scoring and recommendation model. Results of the experiments indicate that in the evolved network using the proposed strategy, concentration indicators such as the Gini coefficient can decrease by up to 17%, and channels ownership of the top 1% of hubs decrease by 27% compared to other autopilot strategies. Moreover, through simulated targeted attacks on hubs and channels, it is shown that by adopting the proposed strategy, the network’s resilience is increased compared to the existing autopilot strategies for evolved networks. The proposed method from this research can also be integrated into operational Lightning clients and potentially replace the current recommendation methods used in Lightning Autopilot.