Lightning Payment Routing via Simulation Graphs and Probing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The Lightning Network faces challenges in determining channel balances due to privacy features, leading to difficulties in optimizing payment routing, increased transaction costs, and suboptimal routing decisions, which hinder its widespread adoption and scalability.
Innovation Solution
A method involving a simulation graph and machine learning models is used to identify optimal routing paths by performing probing transactions and analyzing status messages to update the simulation graph, ensuring accurate representation of Lightning Network nodes and channels, and predicting transaction success probabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If privacy features are implemented in the Lightning Network to protect channel balance information, then user privacy is improved, but the ability to determine channel balances and optimize routing paths deteriorates
Solution Approach 1:
The patent introduces simulation graphs as an intermediary layer that mediates between the private Lightning Network and the routing system. The simulation graph contains simulated nodes and channels that mirror the actual network topology but use public or estimated balance information, allowing routing decisions to be made without exposing real channel balances while still enabling effective pathfinding
Solution Approach 2:
The patent creates a copy of the Lightning Network topology in the form of a simulation graph. This copy includes simulated channels and nodes that replicate the structure of the real network but use public information or machine learning-based estimates for channel balances, enabling routing optimization without requiring access to private balance data
2Productivity
If channel balance information is made transparent to enable optimal routing, then routing efficiency is improved, but user privacy deteriorates
Solution Approach 1:
The simulation graph acts as a mediator that enables routing efficiency without compromising privacy. It provides the routing system with the information needed to make optimal routing decisions (channel topology, estimated capacities) while keeping the actual private balance information hidden in the Lightning Network
Solution Approach 2:
The patent changes the parameters used in the routing simulation from actual private balance values to public or estimated values in the simulation graph. This allows routing algorithms to function with sufficient information while the real private parameters remain protected in the Lightning Network
3Measurement precision
If probing transactions are performed to verify candidate routing paths, then routing accuracy is improved, but transaction costs and network load increase
Solution Approach 1:
The patent performs probing transactions selectively rather than exhaustively. It first identifies candidate routing paths through simulation graph analysis, then performs limited probing transactions only on the most promising candidates to verify their validity, rather than probing all possible paths or performing exhaustive verification
Solution Approach 2:
The patent performs preliminary routing path identification using the simulation graph before executing actual probing transactions. This preliminary filtering step reduces the number of candidate paths that require expensive probing transactions, thereby reducing overall transaction costs and network load
Data Source
AI summary
Disclosed herein are techniques for identifying routing paths between nodes. According to some embodiments, a method can include the steps of (1) receiving, from a client computing device, a request for a routing path between a source node, at least one intermediate node, and a destination node, wherein the request references the source and destination nodes, and includes at least one transaction parameter, (2) referencing the request against at least one simulation graph to identify a plurality of candidate routing paths, (3) identifying the routing path among the plurality of candidate routing paths, and (4) providing the routing path to the client computing device to enable the client computing device to effect a transaction facilitated by the source node, the at least one intermediate node, and the destination node, in accordance with the routing path and the at least one transaction parameter.