<oembed><type>rich</type><version>1.0</version><author_name>npub1e46n428mcyfwznl7nlsf6d3s7rhlwm9x3cmkuqzt3emmdpadmkaqqjxmcu</author_name><author_url>https://nostr.ae/npub1e46n428mcyfwznl7nlsf6d3s7rhlwm9x3cmkuqzt3emmdpadmkaqqjxmcu</author_url><provider_name>njump</provider_name><provider_url>https://nostr.ae</provider_url><html>📅 Original date posted:2022-09-23&#xA;📝 Original message:&#xA;Two questions -&#xA;a) How much gossip overhead do you expect this type of protocol to generate/is there a useful &#xA;outcome for this type of update even if you limit gossip updates to once/twice/thrice per day?&#xA;b) What are the privacy implications of the naive &#34;update on drained channel&#34;, and have you done any &#xA;analysis of the value of this type of gossip update at different levels of privacy?&#xA;&#xA;Thanks,&#xA;Matt&#xA;&#xA;On 9/22/22 2:40 AM, René Pickhardt via Lightning-dev wrote:&#xA;&gt; Good morning fellow Lightning Developers,&#xA;&gt; &#xA;&gt; I am pleased to share my most recent research results [1] with you. They may (if at all) only have a &#xA;&gt; small impact on protocol development / specification but are actually mainly of concern to node &#xA;&gt; operators and LSPs. I still thought they may be relevant for the list.&#xA;&gt; &#xA;&gt; While trying to estimate the expected liquidity distribution in depleted channels due to drain via &#xA;&gt; Markov Models I realized that we can exploit the `htlc_maxium_msat` setting to act as a control &#xA;&gt; valve and regulate the &#34;pressure&#34; coming from the drain and mitigate the depletion of channels. Such &#xA;&gt; ideas are btw not novel at all and heavily used in fluid networks [2]. Thus it seems very natural &#xA;&gt; that we do the same on the Lightning Network.&#xA;&gt; &#xA;&gt; In the article we show within a theoretic model how expected payment failure rates per channel may &#xA;&gt; drop significantly by up to an order of magnitude if channels set up proper asymmetric &#xA;&gt; `htlc_maximum_msat` pairs.&#xA;&gt; &#xA;&gt; We furthermore provide in our iPython notebook [3] two experimental algorithmic ideas with which &#xA;&gt; node operators can find decent `htlc_maximum_msat` values in a greedy fashion. One of the algorithms &#xA;&gt; does not even require to know the drain or payment size distribution or build the Markov model but &#xA;&gt; just looks at the liquidity distribution in the channel at the last x routing attempts and adjusts &#xA;&gt; the `htlc_maximum_msat` value if the distribution is to far away from a uniform distribution.&#xA;&gt; &#xA;&gt; Looking forwards for your thoughts and feedback.&#xA;&gt; &#xA;&gt; with kind regards Rene&#xA;&gt; &#xA;&gt; &#xA;&gt; [1]: &#xA;&gt; https://blog.bitmex.com/the-power-of-htlc_maximum_msat-as-a-control-valve-for-better-flow-control-improved-reliability-and-lower-expected-payment-failure-rates-on-the-lightning-network/ &lt;https://blog.bitmex.com/the-power-of-htlc_maximum_msat-as-a-control-valve-for-better-flow-control-improved-reliability-and-lower-expected-payment-failure-rates-on-the-lightning-network/&gt;&#xA;&gt; [2]: https://en.wikipedia.org/wiki/Control_valve &lt;https://en.wikipedia.org/wiki/Control_valve&gt;&#xA;&gt; [3]: &#xA;&gt; https://github.com/lnresearch/Flow-Control-on-Lightning-Network-Channels-with-Drain-via-Control-Valves/blob/main/htlc_maximum_msat%20as%20a%20valve%20for%20flow%20control%20on%20the%20Lightnig%20network.ipynb &lt;https://github.com/lnresearch/Flow-Control-on-Lightning-Network-Channels-with-Drain-via-Control-Valves/blob/main/htlc_maximum_msat%20as%20a%20valve%20for%20flow%20control%20on%20the%20Lightnig%20network.ipynb&gt;&#xA;&gt; &#xA;&gt; -- &#xA;&gt; https://ln.rene-pickhardt.de &lt;https://ln.rene-pickhardt.de&gt;&#xA;&gt; &#xA;&gt; _______________________________________________&#xA;&gt; Lightning-dev mailing list&#xA;&gt; Lightning-dev at lists.linuxfoundation.org&#xA;&gt; https://lists.linuxfoundation.org/mailman/listinfo/lightning-dev</html></oembed>