pub(crate) fn get_route<L: Deref, S: Score>(
our_node_pubkey: &PublicKey, payment_params: &PaymentParameters, network_graph: &ReadOnlyNetworkGraph,
first_hops: Option<&[&ChannelDetails]>, final_value_msat: u64, final_cltv_expiry_delta: u32,
- logger: L, scorer: &S, random_seed_bytes: &[u8; 32]
+ logger: L, scorer: &S, _random_seed_bytes: &[u8; 32]
) -> Result<Route, LightningError>
where L::Target: Logger {
let payee_node_id = NodeId::from_pubkey(&payment_params.payee_pubkey);
// 4. See if we managed to collect paths which aggregately are able to transfer target value
// (not recommended value).
// 5. If yes, proceed. If not, fail routing.
- // 6. Randomly combine paths into routes having enough to fulfill the payment. (TODO: knapsack)
- // 7. Of all the found paths, select only those with the lowest total fee.
- // 8. The last path in every selected route is likely to be more than we need.
- // Reduce its value-to-transfer and recompute fees.
- // 9. Choose the best route by the lowest total fee.
+ // 6. Select the paths which have the lowest cost (fee plus scorer penalty) per amount
+ // transferred up to the transfer target value.
+ // 7. Reduce the value of the last path until we are sending only the target value.
+ // 8. If our maximum channel saturation limit caused us to pick two identical paths, combine
+ // them so that we're not sending two HTLCs along the same path.
// As for the actual search algorithm,
// we do a payee-to-payer pseudo-Dijkstra's sorting by each node's distance from the payee
return Err(LightningError{err: "Failed to find a sufficient route to the given destination".to_owned(), action: ErrorAction::IgnoreError});
}
- // Sort by total fees and take the best paths.
- payment_paths.sort_unstable_by_key(|path| path.get_total_fee_paid_msat());
- if payment_paths.len() > 50 {
- payment_paths.truncate(50);
- }
+ // Step (6).
+ let mut selected_route = payment_paths;
- // Draw multiple sufficient routes by randomly combining the selected paths.
- let mut drawn_routes = Vec::new();
- let mut prng = ChaCha20::new(random_seed_bytes, &[0u8; 12]);
- let mut random_index_bytes = [0u8; ::core::mem::size_of::<usize>()];
+ debug_assert_eq!(selected_route.iter().map(|p| p.get_value_msat()).sum::<u64>(), already_collected_value_msat);
+ let mut overpaid_value_msat = already_collected_value_msat - final_value_msat;
- let num_permutations = payment_paths.len();
- for _ in 0..num_permutations {
- let mut cur_route = Vec::<PaymentPath>::new();
- let mut aggregate_route_value_msat = 0;
+ // First, sort by the cost-per-value of the path, dropping the paths that cost the most for
+ // the value they contribute towards the payment amount.
+ // We sort in descending order as we will remove from the front in `retain`, next.
+ selected_route.sort_unstable_by(|a, b|
+ (((b.get_cost_msat() as u128) << 64) / (b.get_value_msat() as u128))
+ .cmp(&(((a.get_cost_msat() as u128) << 64) / (a.get_value_msat() as u128)))
+ );
- // Step (6).
- // Do a Fisher-Yates shuffle to create a random permutation of the payment paths
- for cur_index in (1..payment_paths.len()).rev() {
- prng.process_in_place(&mut random_index_bytes);
- let random_index = usize::from_be_bytes(random_index_bytes).wrapping_rem(cur_index+1);
- payment_paths.swap(cur_index, random_index);
+ // We should make sure that at least 1 path left.
+ let mut paths_left = selected_route.len();
+ selected_route.retain(|path| {
+ if paths_left == 1 {
+ return true
+ }
+ let path_value_msat = path.get_value_msat();
+ if path_value_msat <= overpaid_value_msat {
+ overpaid_value_msat -= path_value_msat;
+ paths_left -= 1;
+ return false;
}
+ true
+ });
+ debug_assert!(selected_route.len() > 0);
+ if overpaid_value_msat != 0 {
// Step (7).
- for payment_path in &payment_paths {
- cur_route.push(payment_path.clone());
- aggregate_route_value_msat += payment_path.get_value_msat();
- if aggregate_route_value_msat > final_value_msat {
- // Last path likely overpaid. Substract it from the most expensive
- // (in terms of proportional fee) path in this route and recompute fees.
- // This might be not the most economically efficient way, but fewer paths
- // also makes routing more reliable.
- let mut overpaid_value_msat = aggregate_route_value_msat - final_value_msat;
-
- // First, we drop some expensive low-value paths entirely if possible, since fewer
- // paths is better: the payment is less likely to fail. In order to do so, we sort
- // by value and fall back to total fees paid, i.e., in case of equal values we
- // prefer lower cost paths.
- cur_route.sort_unstable_by(|a, b| {
- a.get_value_msat().cmp(&b.get_value_msat())
- // Reverse ordering for cost, so we drop higher-cost paths first
- .then_with(|| b.get_cost_msat().cmp(&a.get_cost_msat()))
- });
-
- // We should make sure that at least 1 path left.
- let mut paths_left = cur_route.len();
- cur_route.retain(|path| {
- if paths_left == 1 {
- return true
- }
- let mut keep = true;
- let path_value_msat = path.get_value_msat();
- if path_value_msat <= overpaid_value_msat {
- keep = false;
- overpaid_value_msat -= path_value_msat;
- paths_left -= 1;
- }
- keep
- });
-
- if overpaid_value_msat == 0 {
- break;
- }
+ // Now, subtract the remaining overpaid value from the most-expensive path.
+ // TODO: this could also be optimized by also sorting by feerate_per_sat_routed,
+ // so that the sender pays less fees overall. And also htlc_minimum_msat.
+ selected_route.sort_unstable_by(|a, b| {
+ let a_f = a.hops.iter().map(|hop| hop.0.candidate.fees().proportional_millionths as u64).sum::<u64>();
+ let b_f = b.hops.iter().map(|hop| hop.0.candidate.fees().proportional_millionths as u64).sum::<u64>();
+ a_f.cmp(&b_f).then_with(|| b.get_cost_msat().cmp(&a.get_cost_msat()))
+ });
+ let expensive_payment_path = selected_route.first_mut().unwrap();
- assert!(cur_route.len() > 0);
-
- // Step (8).
- // Now, subtract the overpaid value from the most-expensive path.
- // TODO: this could also be optimized by also sorting by feerate_per_sat_routed,
- // so that the sender pays less fees overall. And also htlc_minimum_msat.
- cur_route.sort_unstable_by_key(|path| { path.hops.iter().map(|hop| hop.0.candidate.fees().proportional_millionths as u64).sum::<u64>() });
- let expensive_payment_path = cur_route.first_mut().unwrap();
-
- // We already dropped all the small value paths above, meaning all the
- // remaining paths are larger than remaining overpaid_value_msat.
- // Thus, this can't be negative.
- let expensive_path_new_value_msat = expensive_payment_path.get_value_msat() - overpaid_value_msat;
- expensive_payment_path.update_value_and_recompute_fees(expensive_path_new_value_msat);
- break;
- }
- }
- drawn_routes.push(cur_route);
+ // We already dropped all the paths with value below `overpaid_value_msat` above, thus this
+ // can't go negative.
+ let expensive_path_new_value_msat = expensive_payment_path.get_value_msat() - overpaid_value_msat;
+ expensive_payment_path.update_value_and_recompute_fees(expensive_path_new_value_msat);
}
- // Step (9).
- // Select the best route by lowest total cost.
- drawn_routes.sort_unstable_by_key(|paths| paths.iter().map(|path| path.get_cost_msat()).sum::<u64>());
- let selected_route = drawn_routes.first_mut().unwrap();
-
+ // Step (8).
// Sort by the path itself and combine redundant paths.
// Note that we sort by SCIDs alone as its simpler but when combining we have to ensure we
// compare both SCIDs and NodeIds as individual nodes may use random aliases causing collisions
projects / rust-lightning / blobdiff