This is an opinion piece by Shinobi, a self-taught educator in the Bitcoin space and tech-oriented Bitcoin podcast host.
The Lightning Network as a payment routing network has many similarities to the Internet itself. You must be connected to the network, payments are routed from a source node on the network to a destination node just like data packets on the internet and this requires an uninterrupted connection from source to destination. It also has a huge difference – the liquidity requirement. On the Internet, as long as bandwidth is available (i.e. the pipes are not “clogged”), you can pass an infinite amount of information along a route as long as you have enough time to wait for them to pass. Lightning channels, however, can run out, as they actually require moving money from one side of a channel to another in order to route a payment, and eventually they will run out of money on one side. and push it all the other way.
This creates a necessary balance between using the network in the present to transfer payments for individual users and the health of the network in the future in terms of its ability to transfer payments for other users. Each time someone routes a payment through a specific channel, it increases the likelihood that the channel they used may not be able to process payments in the same direction for other users in the future.
Essentially, users attempting to adopt en masse strategies to get away with guaranteeing their payment delivery can adversely affect the overall distribution of network liquidity and actually reduce the likelihood that payments from individual users successfully arrive at their destination. Essentially, whatever strategy end users primarily use to select routes for their payments will have systemic effects across the entire network. In the negative sense, that is, how individual behaviors have degrading effects on the system as a whole, this dynamic is known as the “price of anarchy”.
Rene Pickhardt has engaged in a line of research to develop useful heuristics to improve the reliability of payment delivery over the Lightning Network. One strategy to achieve the goal derived from this research is called “Pickhardt payments”. Currently, the most frequently used strategy on the network is to prioritize route selection based on the lowest charges. It works pretty well for small payments, but not so much for large amounts. Intuitively, the reason should be obvious: these low-cost routes are widely used, which tends to push liquidity in one direction, leaving less liquidity available. The effect this has for other small payments taking the same path is small until exhaustion is approached, but for larger amounts the chances of success become lower.
Pickhardt payments work by prioritizing reliability over cheapness, making educated guesses about the likelihood that a payment will succeed on different potential paths it might take. Much like the dominant low-cost prioritization strategy, over time as a node attempts to make payments and sees some fail, it will update its assumptions about the probability of payment success and refine over time its precision. This should help prevent swarm nodes from always exhausting the same channels, as their view of the network in terms of reliability will evolve in unique ways over time.
An important part of path selection is considering which direction liquidity is flowing through a channel. Is it balanced both ways? Is it mostly unidirectional? In his most recent research examining the dynamics of the price of anarchy, Pickhardt noted that he realized that, based on public gossip data, it might be possible to estimate the drain rate in the channels , how balanced or unbalanced the flow through them is and further improve the reliability of estimates of the success or failure of payments along certain routes. Estimating this correctly allows you to look at a channel and guess which direction has a high probability of making a payout and which direction has a low probability.
Another aspect of Pickhardt payments is to optimize for both reliability and reduced costs. In modeling things to study the price of the anarchic dynamics of the Lightning Network, it was discovered that optimizing both reliability and royalties result in one of the worst externality costs to the network or the highest price of anarchy. This appears to create the highest network channel exhaustion rate of all path selection strategies.
But these effects do not exist in a vacuum or without counterweights. Routing nodes on the network are also actors who have tools and can adopt strategies to optimize flow control and counterbalance it. Routing nodes can change fees to discourage pushing liquidity to one side of a channel, i.e. if most payments are flowing in one direction, they can charge a higher fee for it and lower fees to go the other way. Nodes can open or close channels, creating new connections to meet higher demand. Nodes can also rebalance channels, pushing liquidity from one of their channels to the network and to another channel to change the distribution of liquidity in that channel. Nodes sending payments can also select and use different path selection strategies when they find that the current one leads to frequent payment failures.
I’m sure people reading right now are thinking something along the lines of, “Fuck it, the market will fix it, Lightning is a market-driven system.” Lightning is almost entirely a market-driven system, but it’s not that straightforward when it comes to analyzing dynamics like the Price of Anarchy. Network users will not manually analyze routing algorithms, picking and choosing what to use with each payment; They are going to use tools and software that automate all of this and hide it in the background. This makes this type of research important to the overall health of the network. A way must be found to allow end users to engage with the network selfishly, putting their own interests first, without degrading the performance of the network as a whole.
Modeling how these two dynamics interact, sending node strategies and mitigation strategies for routing nodes are extremely important in developing strategies for both classes of users to balance and optimize overall health. of the network and the reliability of payments for individual users. Routing data between different devices is a long-solved computing problem on which the Lightning Network relies heavily, but the dynamics of liquidity constraints add a new facet to the whole field of research around reliable data routing. information.
So far, the Lightning Network has been a huge success in improving the speed and scalability of payments using Bitcoin, but to continue that success on a larger scale and with a greater load of from a greater number of users, the interaction of these two different dynamics must be fully understood and accounted for. For network users to adopt effective strategies, these strategies must first be developed, understood and verified.
This is a guest post from Shinobi. The opinions expressed are entirely their own and do not necessarily reflect those of BTC Inc or Bitcoin Magazine.