routing: limit capacity factor and tune parameters

* The maximal reduction in the probability is limited to 0.5 (previously
  ~0.05), such that we don't get too low apriori probabilities.
  Otherwise, this may lead to a too strong selection of large (and maybe
  expensive) channels. A two-hop path would get total probability
  penalties of:

  - 1000PPM/(0.6*0.6) = 2778 PPM in the unsaturated case
  - 1000PPM/(0.6*(0.6*0.5)) = 5556 PPM in the saturated case, where the
    second hop is saturated

  The difference in PPM of 2778 PPM should be enough to bias towards the
  first path.

* The smearing factor is reduced. Previously we had to keep a higher
  smearing factor in order to make the capacity factor not go to zero
  for high amounts, to still give a fully saturated channel a chance.
  This is not needed anymore due to the capping to 0.5. A lower value of
  the smearing factor lets us more precisely choose a capacity fraction
  and the capacity factor is more neutral when it comes to intermediate
  amounts.

We set a conservative default value for the capacity fraction, which
still has the effect of discarding exhausted channels, giving a
noticeable effect when about 90% of the capacity is being used.

routing/probability_apriori.go

@@ -16,31 +16,24 @@ const (
 	// capacity-related probability reweighting works. CapacityFraction
 	// defines the fraction of the channel capacity at which the effect
 	// roughly sets in and capacitySmearingFraction defines over which range
-	// the factor changes from 1 to 0.
+	// the factor changes from 1 to minCapacityFactor.
-	//
-	// We may fall below the minimum required probability
-	// (DefaultMinRouteProbability) when the amount comes close to the
-	// available capacity of a single channel of the route in case of no
-	// prior knowledge about the channels. We want such routes still to be
-	// available and therefore a probability reduction should not completely
-	// drop the total probability below DefaultMinRouteProbability.
-	// For this to hold for a three-hop route we require:
-	// (DefaultAprioriHopProbability)^3 * minCapacityFactor >
-	//      DefaultMinRouteProbability
-	//
-	// For DefaultAprioriHopProbability = 0.6 and
-	// DefaultMinRouteProbability = 0.01 this results in
-	// minCapacityFactor ~ 0.05. The following combination of parameters
-	// fulfill the requirement with capacityFactor(cap, cap) ~ 0.076 (see
-	// tests).
 
 	// DefaultCapacityFraction is the default value for CapacityFraction.
-	DefaultCapacityFraction = 0.75
+	// It is chosen such that the capacity factor is active but with a small
+	// effect. This value together with capacitySmearingFraction leads to a
+	// noticeable reduction in probability if the amount starts to come
+	// close to 90% of a channel's capacity.
+	DefaultCapacityFraction = 0.9999
 
-	// We don't want to have a sharp drop of the capacity factor to zero at
+	// capacitySmearingFraction defines how quickly the capacity factor
-	// capacityCutoffFraction, but a smooth smearing such that some residual
+	// drops from 1 to minCapacityFactor. This value results in about a
-	// probability is left when spending the whole amount, see above.
+	// variation over 20% of the capacity.
-	capacitySmearingFraction = 0.1
+	capacitySmearingFraction = 0.025
+
+	// minCapacityFactor is the minimal value the capacityFactor can take.
+	// Having a too low value can lead to discarding of paths due to the
+	// enforced minimal proability or to too high pathfinding weights.
+	minCapacityFactor = 0.5
 
 	// minCapacityFraction is the minimum allowed value for
 	// CapacityFraction. The success probability in the random balance model
@@ -265,10 +258,13 @@ func (p *AprioriEstimator) getWeight(age time.Duration) float64 {
 }
 
 // capacityFactor is a multiplier that can be used to reduce the probability
-// depending on how much of the capacity is sent. The limits are 1 for amt == 0
+// depending on how much of the capacity is sent. In other words, the factor
-// and 0 for amt >> cutoffMsat. The function drops significantly when amt
+// sorts out channels that don't provide enough liquidity. Effectively, this
-// reaches cutoffMsat. smearingMsat determines over which scale the reduction
+// leads to usage of larger channels in total to increase success probability,
-// takes place.
+// but it may also increase fees. The limits are 1 for amt == 0 and
+// minCapacityFactor for amt >> capacityCutoffFraction. The function drops
+// significantly when amt reaches cutoffMsat. smearingMsat determines over which
+// scale the reduction takes place.
 func capacityFactor(amt lnwire.MilliSatoshi, capacity btcutil.Amount,
 	capacityCutoffFraction float64) float64 {
 
@@ -299,7 +295,11 @@ func capacityFactor(amt lnwire.MilliSatoshi, capacity btcutil.Amount,
 	// at cutoffMsat, decaying over the smearingMsat scale.
 	denominator := 1 + math.Exp(-(amtMsat-cutoffMsat)/smearingMsat)
 
-	return 1 - 1/denominator
+	// The numerator decides what the minimal value of this function will
+	// be. The minimal value is set by minCapacityFactor.
+	numerator := 1 - minCapacityFactor
+
+	return 1 - numerator/denominator
 }
 
 // PairProbability estimates the probability of successfully traversing to

routing/probability_apriori_test.go

@@ -28,11 +28,12 @@ const (
 
 	// testCapacity is used to define a capacity for some channels.
 	testCapacity         = btcutil.Amount(100_000)
-	testAmount           = lnwire.MilliSatoshi(50_000_000)
+	testAmount           = lnwire.MilliSatoshi(90_000_000)
-	testCapacityFraction = 0.75
+	testCapacityFraction = 0.9999
 
-	// Defines the capacityFactor for testAmount and testCapacity.
+	// capFactor is the capacityFactor for testAmount, testCapacity and
-	capFactor = 0.9241
+	// testCapacityFraction.
+	capFactor = 0.9909715
 )
 
 type estimatorTestContext struct {
@@ -244,13 +245,13 @@ func TestCapacityCutoff(t *testing.T) {
 			name:             "low amount",
 			capacityFraction: 0.75,
 			amountMsat:       capacityMSat / 10,
-			expectedFactor:   0.998,
+			expectedFactor:   1,
 		},
 		{
 			name:             "half amount",
 			capacityFraction: 0.75,
 			amountMsat:       capacityMSat / 2,
-			expectedFactor:   0.924,
+			expectedFactor:   1,
 		},
 		{
 			name:             "cutoff amount",
@@ -258,13 +259,13 @@ func TestCapacityCutoff(t *testing.T) {
 			amountMsat: int(
 				0.75 * float64(capacityMSat),
 			),
-			expectedFactor: 0.5,
+			expectedFactor: 0.75,
 		},
 		{
 			name:             "high amount",
 			capacityFraction: 0.75,
 			amountMsat:       capacityMSat * 80 / 100,
-			expectedFactor:   0.377,
+			expectedFactor:   0.560,
 		},
 		{
 			// Even when we spend the full capacity, we still want
@@ -274,7 +275,7 @@ func TestCapacityCutoff(t *testing.T) {
 			name:             "full amount",
 			capacityFraction: 0.75,
 			amountMsat:       capacityMSat,
-			expectedFactor:   0.076,
+			expectedFactor:   0.5,
 		},
 		{
 			name:             "more than capacity",
@@ -282,6 +283,28 @@ func TestCapacityCutoff(t *testing.T) {
 			amountMsat:       capacityMSat + 1,
 			expectedFactor:   0.0,
 		},
+		// Default CapacityFactor of 0.9999.
+		{
+			name:             "zero amount",
+			capacityFraction: 0.9999,
+			amountMsat:       0,
+			expectedFactor:   1.00,
+		},
+		{
+			name:             "90% of the channel capacity",
+			capacityFraction: 0.9999,
+			amountMsat:       capacityMSat * 90 / 100,
+			expectedFactor:   0.990,
+		},
+		{
+			// We won't saturate at 0.5 as in the other case but at
+			// a higher value of 0.75 due to the smearing, this
+			// translates to a penalty increase of a factor of 1.33.
+			name:             "full amount",
+			capacityFraction: 0.9999,
+			amountMsat:       capacityMSat,
+			expectedFactor:   0.75,
+		},
 		// Inactive capacity factor.
 		{
 			name:             "inactive capacity factor",