Mapping Lightning Network Part 2: Node Centrality and Stability

The Lightning Network’s decentralized architecture thrives on the intricate connectivity and distinct roles of its individual nodes. Each node, whether a modest participant or a critical hub, plays a part in ensuring the network’s stability, efficiency, and capacity for seamless transactions. Understanding the dynamics of these nodes is vital for optimizing routing, enhancing resilience, and sustaining the decentralized principles that underpin the network.

Building on our initial analysis of node metrics, this exploration focuses on centrality metrics, with particular attention to graph centrality and reachability within one and two hops. These metrics provide a detailed view of how nodes interconnect and how efficiently transactions can traverse the network. By identifying nodes that act as key facilitators of routing and connectivity, we can uncover the mechanisms that maintain the network’s robustness without relying on centralized structures.

Examining centrality and reachability not only highlights the importance of well-positioned nodes but also demonstrates the LN’s ability to balance decentralization with operational efficiency. This balance is essential for supporting its ever-expanding user base and enabling the low-cost, high-speed transactions that define the Lightning Network.

Additionally, our analysis also examines closed channels metrics, offering insights into network stability by tracking the frequency and patterns of channel closures. These metrics help distinguish between nodes that maintain stable operations and those undergoing frequent changes, providing insights into their reliability and overall behavior within the network.

Data Cleaning

As detailed in the previous article, a comprehensive data-cleaning process was implemented to focus on active and relevant nodes. Nodes with fewer than two channels were excluded, refining the original dataset of 14,142 nodes to a more manageable and meaningful subset of 5,122. This approach ensured the analysis targeted nodes actively contributing to the network’s transaction flow.

To improve clarity and reduce potential biases, visualizations were limited to data points below specific percentiles. By minimizing the impact of extreme outliers, this method brought broader network trends into sharper focus, delivering a more accurate and representative picture of the Lightning Network's overall structure and dynamics.

Centrality Metrics: Graph Centrality and Reachability

Centrality metrics play a crucial role in understanding how effectively each node contributes to the Lightning Network’s connectivity and routing efficiency. These metrics highlight a node’s position within the network and its ability to connect with others, shedding light on its importance in maintaining smooth transaction flow and overall network stability. 

This analysis focuses on two key aspects: closeness centrality, which measures how quickly a node can access other nodes, and reachability within a specified number of hops, revealing how far a node’s influence extends across the network. Together, these metrics provide valuable insights into the network's structure and the pivotal roles certain nodes play in ensuring its resilience and performance.

Closeness Centrality

Closeness centrality measures how quickly and efficiently a node can connect to others in the Lightning Network. Per our research, most nodes exhibit similar closeness centrality values, indicating a relatively homogeneous connectivity structure across the network. More than 50% of the nodes have a closeness centrality above 0.292, meaning they can reach a significant portion of the network with minimal hops. Nodes scoring near 0.40 are generally well-connected hubs, which, while not at a theoretical maximum of 1, still play a significant role in streamlining network traffic.

Nodes with a closeness centrality of zero likely represent isolated nodes with little or no connectivity to the broader network. The absence of extremely high centrality nodes (closer to 1) suggests that the Lightning Network maintains a decentralized structure, lacking highly dominant hubs, which enhances its resilience and aligns with decentralized network principles.

Reachability within X Hops

Reachability within one hop highlights the extent of a node’s direct connections within the Lightning Network. For the analyzed 5,122 nodes, the number of nodes reachable within one hop was calculated using the raw LN graph, which initially contained 14,142 nodes. 

Our analysis shows that roughly half of the nodes can directly connect to more than 1,835 other nodes, reflecting a moderate level of connectivity across the network. The most connected 25% of nodes, however, can reach 3,000 or more nodes in a single hop, positioning them as critical hubs that support the network's overall structure and efficiency. At the other end of the spectrum, some nodes with only one or two connections contribute minimally to the network's reachability, serving a limited role in the broader system.

In terms of two-hop reachability, the average node can connect to about 6,066 other nodes, significantly extending its effective reach across a large section of the network. Notably, as many as 25% of nodes are capable of accessing over 7,526 nodes within two hops, underscoring the network’s strong connectivity across multiple layers. This two-hop structure ensures that even nodes without direct connections are within reach of a significant part of the network, strengthening its overall robustness and improving accessibility for efficient transaction routing.

Together, these closeness centrality and reachability metrics illustrate a well-connected and moderately decentralized network, where a balance of moderately central nodes and a few highly connected hubs maintain transaction efficiency without overly centralizing power. 

Closed Channels Metrics: Understanding Network Stability

Closed channels offer valuable insights into the operational dynamics and stability of nodes within the Lightning Network. Tracking the number of closed channels over a month provides a clear view of how frequently nodes alter their connections, shedding light on the stability or volatility of their activity.

Number of Closed Channels per Month

Our analysis revealed that channel closures are relatively rare across the network. Over 3,000 nodes—representing the majority—reported no closed channels within a month, highlighting stable operations with consistent connections. This stability underscores the resilience of many nodes, as they maintain their routing capacity and liquidity without frequent disruptions.

At the other end of the spectrum, a few nodes experienced up to 803 channel closures within the same timeframe. These outliers likely represent either highly active participants, such as nodes experimenting with optimizing routes and liquidity, or nodes struggling with instability, frequently opening and closing channels due to operational or strategic shifts.

Key Takeaways

• Network-wide stability: The low frequency of channel closures indicates that most nodes contribute to a stable and predictable network environment.
• Active vs. volatile nodes: While some nodes demonstrate high activity levels, others may face challenges that prompt frequent adjustments to their channels.
• Implications for routing: Nodes with zero or minimal closures are reliable for routing, while those with frequent closures may signal potential volatility, impacting their dependability as routing partners.

The closed channel metric provides valuable insights into how nodes behave, highlighting those that consistently perform well and others that frequently change their strategies. By analyzing these patterns, we can better assess the network’s overall stability and optimize routing decisions.

Conclusion

The analysis highlights the Lightning Network's decentralized and resilient structure, where nodes collectively maintain connectivity and efficiency. The lack of extremely high centrality nodes reflects the network's adherence to decentralization principles, avoiding reliance on dominant hubs. This distributed architecture also enhances the network's robustness and ensures stable operations across a wide range of participants.

Reachability metrics emphasize the network’s strong connectivity. Around half of the nodes can directly connect to more than 1,835 other nodes in a single hop, while the top 25% can reach 3,000 or more, making these nodes critical hubs in the system.

Extending the analysis to two-hop reachability, the average node connects to approximately 6,000 others, while the top-performing 25% can reach over 7,500 nodes. These findings illustrate a well-connected and moderately decentralized network, where a combination of moderately central nodes and highly connected hubs ensures transaction efficiency without compromising the network’s decentralized ethos.

Meanwhile, channel closure metrics provide further insight into network behavior and stability. The majority of nodes—over 3,000—reported no closed channels in a month, reflecting stable and reliable operations. However, a small number of nodes experienced frequent channel closures, suggesting either dynamic activity or potential instability. These patterns reveal a balance within the network, where most nodes maintain consistent connections while others actively manage their channels to adapt to changing conditions.

Together, the metrics explored—centrality, reachability, and closed channel behavior—paint a comprehensive picture of the Lightning Network's operational strengths and areas of complexity. These insights will be critical as the network evolves, ensuring its robustness, optimizing routing strategies, and sustaining its decentralized design.

Building on this foundation, future research can apply these metrics to develop advanced tools, including machine learning models, to further refine routing strategies and maximize the network’s potential. 

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