This program is a recommendation engine for lightning network node operators.

It analyzes the public network graph and makes recommendations to which channels a node operator should open channels. It will also suggest the capacity of the channels that are recommended.

Currently the library does not use any private information like previous routing successes or failures.

lib_autopilot.py is the core of the project:

lib_autopilot is a library which based on a networkx graph tries to predict which channels should be added for a new node on the network. The long term is to generate a lightning network with good topological properties. This library currently uses 4 heuristics to select channels and supports two strategies for combining those heuristics.

1.) Diverse: which tries to to get nodes from every distribution 2.) Merge: which builds the mixture distribution of the 4 heuristics

The library also estimates how much funds should be used for every newly added channel. This is achieved by looking at the average channel capacity of the suggested channel partners. A probability distribution which is proportional to those capacities is created and smoothed with the uniform distribution.

The 4 heuristics for channel partner suggestion are:

1.) Random: following the Erdoes Renyi model nodes are drawn from a uniform distribution 2.) Central: nodes are sampled from a distribution proportional to the betweeness centrality of nodes 3.) Decrease Diameter: nodes are sampled from distribution of the nodes which favors badly connected nodes 4.) Richness: nodes with high liquidity are taken and it is sampled from a uniform distribution of those

Who uses lib_autopilot

• Currently c-lightning by blockstream maintains a plugin which uses lib_autopilot. Checkout their repository
• Electrum has showed interest in using lib_autopilot for their lightning network implementation

other autopilots:

• lnbig has published a javascript autopilot: https://gist.github.com/LNBIG-COM/dfe5d25bcea25612c559e02fd7698660
• lnd uses an autopilot in their software. Someone could write a go wrapper for lib_autopilot.py

Future work

The library is supposed to be extended by a simulation framework which can be used to evaluate which strategies are useful on the long term. For this heavy computations (like centrality measures) might have to be reimplemented in a more dynamic way. Also it is important to understand that this program is not optimized to run efficiently on large scale graphs with more than 100k nodes or on densly connected graphs. The programm needs the following dependencies: pip install networkx numpy pylightning