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authorMurch <murch@murch.one>2023-05-23 19:36:04 -0400
committerMurch <murch@murch.one>2024-02-09 10:44:32 +0100
commit6cc9a46cd0f4ed80d4523bbef1508142e0c80d27 (patch)
tree7458471f4a9468a2de94179bddda88b4d617c459 /src/wallet/coinselection.cpp
parent89d09566431f57034d9a7df32547ceb13d79c62c (diff)
downloadbitcoin-6cc9a46cd0f4ed80d4523bbef1508142e0c80d27.tar.xz
coinselection: Add CoinGrinder algorithm
CoinGrinder is a DFS-based coin selection algorithm that deterministically finds the input set with the lowest weight creating a change output.
Diffstat (limited to 'src/wallet/coinselection.cpp')
-rw-r--r--src/wallet/coinselection.cpp291
1 files changed, 291 insertions, 0 deletions
diff --git a/src/wallet/coinselection.cpp b/src/wallet/coinselection.cpp
index 570fac6900..20944b3c8d 100644
--- a/src/wallet/coinselection.cpp
+++ b/src/wallet/coinselection.cpp
@@ -188,6 +188,286 @@ util::Result<SelectionResult> SelectCoinsBnB(std::vector<OutputGroup>& utxo_pool
return result;
}
+/*
+ * TL;DR: Coin Grinder is a DFS-based algorithm that deterministically searches for the minimum-weight input set to fund
+ * the transaction. The algorithm is similar to the Branch and Bound algorithm, but will produce a transaction _with_ a
+ * change output instead of a changeless transaction.
+ *
+ * Full description: CoinGrinder can be thought of as a graph walking algorithm. It explores a binary tree
+ * representation of the powerset of the UTXO pool. Each node in the tree represents a candidate input set. The tree’s
+ * root is the empty set. Each node in the tree has two children which are formed by either adding or skipping the next
+ * UTXO ("inclusion/omission branch"). Each level in the tree after the root corresponds to a decision about one UTXO in
+ * the UTXO pool.
+ *
+ * Example:
+ * We represent UTXOs as _alias=[effective_value/weight]_ and indicate omitted UTXOs with an underscore. Given a UTXO
+ * pool {A=[10/2], B=[7/1], C=[5/1], D=[4/2]} sorted by descending effective value, our search tree looks as follows:
+ *
+ * _______________________ {} ________________________
+ * / \
+ * A=[10/2] __________ {A} _________ __________ {_} _________
+ * / \ / \
+ * B=[7/1] {AB} _ {A_} _ {_B} _ {__} _
+ * / \ / \ / \ / \
+ * C=[5/1] {ABC} {AB_} {A_C} {A__} {_BC} {_B_} {__C} {___}
+ * / \ / \ / \ / \ / \ / \ / \ / \
+ * D=[4/2] {ABCD} {ABC_} {AB_D} {AB__} {A_CD} {A_C_} {A__D} {A___} {_BCD} {_BC_} {_B_D} {_B__} {__CD} {__C_} {___D} {____}
+ *
+ *
+ * CoinGrinder uses a depth-first search to walk this tree. It first tries inclusion branches, then omission branches. A
+ * naive exploration of a tree with four UTXOs requires visiting all 31 nodes:
+ *
+ * {} {A} {AB} {ABC} {ABCD} {ABC_} {AB_} {AB_D} {AB__} {A_} {A_C} {A_CD} {A_C_} {A__} {A__D} {A___} {_} {_B} {_BC}
+ * {_BCD} {_BC_} {_B_} {_B_D} {_B__} {__} {__C} {__CD} {__C} {___} {___D} {____}
+ *
+ * As powersets grow exponentially with the set size, walking the entire tree would quickly get computationally
+ * infeasible with growing UTXO pools. Thanks to traversing the tree in a deterministic order, we can keep track of the
+ * progress of the search solely on basis of the current selection (and the best selection so far). We visit as few
+ * nodes as possible by recognizing and skipping any branches that can only contain solutions worse than the best
+ * solution so far. This makes CoinGrinder a branch-and-bound algorithm
+ * (https://en.wikipedia.org/wiki/Branch_and_bound).
+ * CoinGrinder is searching for the input set with lowest weight that can fund a transaction, so for example we can only
+ * ever find a _better_ candidate input set in a node that adds a UTXO, but never in a node that skips a UTXO. After
+ * visiting {A} and exploring the inclusion branch {AB} and its descendants, the candidate input set in the omission
+ * branch {A_} is equivalent to the parent {A} in effective value and weight. While CoinGrinder does need to visit the
+ * descendants of the omission branch {A_}, it is unnecessary to evaluate the candidate input set in the omission branch
+ * itself. By skipping evaluation of all nodes on an omission branch we reduce the visited nodes to 15:
+ *
+ * {A} {AB} {ABC} {ABCD} {AB_D} {A_C} {A_CD} {A__D} {_B} {_BC} {_BCD} {_B_D} {__C} {__CD} {___D}
+ *
+ * _______________________ {} ________________________
+ * / \
+ * A=[10/2] __________ {A} _________ ___________\____________
+ * / \ / \
+ * B=[7/1] {AB} __ __\_____ {_B} __ __\_____
+ * / \ / \ / \ / \
+ * C=[5/1] {ABC} \ {A_C} \ {_BC} \ {__C} \
+ * / / / / / / / /
+ * D=[4/2] {ABCD} {AB_D} {A_CD} {A__D} {_BCD} {_B_D} {__CD} {___D}
+ *
+ *
+ * We refer to the move from the inclusion branch {AB} via the omission branch {A_} to its inclusion-branch child {A_C}
+ * as _shifting to the omission branch_ or just _SHIFT_. (The index of the ultimate element in the candidate input set
+ * shifts right by one: {AB} ⇒ {A_C}.)
+ * When we reach a leaf node in the last level of the tree, shifting to the omission branch is not possible. Instead we
+ * go to the omission branch of the node’s last ancestor on an inclusion branch: from {ABCD}, we go to {AB_D}. From
+ * {AB_D}, we go to {A_C}. We refer to this operation as a _CUT_. (The ultimate element in
+ * the input set is deselected, and the penultimate element is shifted right by one: {AB_D} ⇒ {A_C}.)
+ * If a candidate input set in a node has not selected sufficient funds to build the transaction, we continue directly
+ * along the next inclusion branch. We call this operation _EXPLORE_. (We go from one inclusion branch to the next
+ * inclusion branch: {_B} ⇒ {_BC}.)
+ * Further, any prefix that already has selected sufficient effective value to fund the transaction cannot be improved
+ * by adding more UTXOs. If for example the candidate input set in {AB} is a valid solution, all potential descendant
+ * solutions {ABC}, {ABCD}, and {AB_D} must have a higher weight, thus instead of exploring the descendants of {AB}, we
+ * can SHIFT from {AB} to {A_C}.
+ *
+ * Given the above UTXO set, using a target of 11, and following these initial observations, the basic implementation of
+ * CoinGrinder visits the following 10 nodes:
+ *
+ * Node [eff_val/weight] Evaluation
+ * ---------------------------------------------------------------
+ * {A} [10/2] Insufficient funds: EXPLORE
+ * {AB} [17/3] Solution: SHIFT to omission branch
+ * {A_C} [15/3] Better solution: SHIFT to omission branch
+ * {A__D} [14/4] Worse solution, shift impossible due to leaf node: CUT to omission branch of {A__D},
+ * i.e. SHIFT to omission branch of {A}
+ * {_B} [7/1] Insufficient funds: EXPLORE
+ * {_BC} [12/2] Better solution: SHIFT to omission branch
+ * {_B_D} [11/3] Worse solution, shift impossible due to leaf node: CUT to omission branch of {_B_D},
+ * i.e. SHIFT to omission branch of {_B}
+ * {__C} [5/1] Insufficient funds: EXPLORE
+ * {__CD} [9/3] Insufficient funds, leaf node: CUT
+ * {___D} [4/2] Insufficient funds, leaf node, cannot CUT since only one UTXO selected: done.
+ *
+ * _______________________ {} ________________________
+ * / \
+ * A=[10/2] __________ {A} _________ ___________\____________
+ * / \ / \
+ * B=[7/1] {AB} __\_____ {_B} __ __\_____
+ * / \ / \ / \
+ * C=[5/1] {A_C} \ {_BC} \ {__C} \
+ * / / / /
+ * D=[4/2] {A__D} {_B_D} {__CD} {___D}
+ *
+ *
+ * We implement this tree walk in the following algorithm:
+ * 1. Add `next_utxo`
+ * 2. Evaluate candidate input set
+ * 3. Determine `next_utxo` by deciding whether to
+ * a) EXPLORE: Add next inclusion branch, e.g. {_B} ⇒ {_B} + `next_uxto`: C
+ * b) SHIFT: Replace last selected UTXO by next higher index, e.g. {A_C} ⇒ {A__} + `next_utxo`: D
+ * c) CUT: deselect last selected UTXO and shift to omission branch of penultimate UTXO, e.g. {AB_D} ⇒ {A_} + `next_utxo: C
+ *
+ * The implementation then adds further optimizations by discovering further situations in which either the inclusion
+ * branch can be skipped, or both the inclusion and omission branch can be skipped after evaluating the candidate input
+ * set in the node.
+ *
+ * @param std::vector<OutputGroup>& utxo_pool The UTXOs that we are choosing from. These UTXOs will be sorted in
+ * descending order by effective value, with lower waste preferred as a tie-breaker. (We can think of an output
+ * group with multiple as a heavier UTXO with the combined amount here.)
+ * @param const CAmount& selection_target This is the minimum amount that we need for the transaction without considering change.
+ * @param const CAmount& change_target The minimum budget for creating a change output, by which we increase the selection_target.
+ * @param int max_weight The maximum permitted weight for the input set.
+ * @returns The result of this coin selection algorithm, or std::nullopt
+ */
+util::Result<SelectionResult> CoinGrinder(std::vector<OutputGroup>& utxo_pool, const CAmount& selection_target, CAmount change_target, int max_weight)
+{
+ std::sort(utxo_pool.begin(), utxo_pool.end(), descending);
+
+ // Check that there are sufficient funds
+ CAmount total_available = 0;
+ for (const OutputGroup& utxo : utxo_pool) {
+ // Assert UTXOs with non-positive effective value have been filtered
+ Assume(utxo.GetSelectionAmount() > 0);
+ total_available += utxo.GetSelectionAmount();
+ }
+
+ const CAmount total_target = selection_target + change_target;
+ if (total_available < total_target) {
+ // Insufficient funds
+ return util::Error();
+ }
+
+ // The current selection and the best input set found so far, stored as the utxo_pool indices of the UTXOs forming them
+ std::vector<size_t> curr_selection;
+ std::vector<size_t> best_selection;
+
+ // The currently selected effective amount, and the effective amount of the best selection so far
+ CAmount curr_amount = 0;
+ CAmount best_selection_amount = MAX_MONEY;
+
+ // The weight of the currently selected input set, and the weight of the best selection
+ int curr_weight = 0;
+ int best_selection_weight = std::numeric_limits<int>::max();
+
+ // Whether the input sets generated during this search have exceeded the maximum transaction weight at any point
+ bool max_tx_weight_exceeded = false;
+
+ // Index of the next UTXO to consider in utxo_pool
+ size_t next_utxo = 0;
+
+ /*
+ * You can think of the current selection as a vector of booleans that has decided inclusion or exclusion of all
+ * UTXOs before `next_utxo`. When we consider the next UTXO, we extend this hypothetical boolean vector either with
+ * a true value if the UTXO is included or a false value if it is omitted. The equivalent state is stored more
+ * compactly as the list of indices of the included UTXOs and the `next_utxo` index.
+ *
+ * We can never find a new solution by deselecting a UTXO, because we then revisit a previously evaluated
+ * selection. Therefore, we only need to check whether we found a new solution _after adding_ a new UTXO.
+ *
+ * Each iteration of CoinGrinder starts by selecting the `next_utxo` and evaluating the current selection. We
+ * use three state transitions to progress from the current selection to the next promising selection:
+ *
+ * - EXPLORE inclusion branch: We do not have sufficient funds, yet. Add `next_utxo` to the current selection, then
+ * nominate the direct successor of the just selected UTXO as our `next_utxo` for the
+ * following iteration.
+ *
+ * Example:
+ * Current Selection: {0, 5, 7}
+ * Evaluation: EXPLORE, next_utxo: 8
+ * Next Selection: {0, 5, 7, 8}
+ *
+ * - SHIFT to omission branch: Adding more UTXOs to the current selection cannot produce a solution that is better
+ * than the current best, e.g. the current selection weight exceeds the max weight or
+ * the current selection amount is equal to or greater than the target.
+ * We designate our `next_utxo` the one after the tail of our current selection, then
+ * deselect the tail of our current selection.
+ *
+ * Example:
+ * Current Selection: {0, 5, 7}
+ * Evaluation: SHIFT, next_utxo: 8, omit last selected: {0, 5}
+ * Next Selection: {0, 5, 8}
+ *
+ * - CUT entire subtree: We have exhausted the inclusion branch for the penultimately selected UTXO, both the
+ * inclusion and the omission branch of the current prefix are barren. E.g. we have
+ * reached the end of the UTXO pool, so neither further EXPLORING nor SHIFTING can find
+ * any solutions. We designate our `next_utxo` the one after our penultimate selected,
+ * then deselect both the last and penultimate selected.
+ *
+ * Example:
+ * Current Selection: {0, 5, 7}
+ * Evaluation: CUT, next_utxo: 6, omit two last selected: {0}
+ * Next Selection: {0, 6}
+ */
+ auto deselect_last = [&]() {
+ OutputGroup& utxo = utxo_pool[curr_selection.back()];
+ curr_amount -= utxo.GetSelectionAmount();
+ curr_weight -= utxo.m_weight;
+ curr_selection.pop_back();
+ };
+
+ SelectionResult result(selection_target, SelectionAlgorithm::CG);
+ size_t curr_try = 0;
+ while (true) {
+ bool should_shift{false}, should_cut{false};
+ // Select `next_utxo`
+ OutputGroup& utxo = utxo_pool[next_utxo];
+ curr_amount += utxo.GetSelectionAmount();
+ curr_weight += utxo.m_weight;
+ curr_selection.push_back(next_utxo);
+ ++next_utxo;
+ ++curr_try;
+
+ // EVALUATE current selection: check for solutions and see whether we can CUT or SHIFT before EXPLORING further
+ if (curr_weight > max_weight) {
+ // max_weight exceeded: SHIFT
+ max_tx_weight_exceeded = true;
+ should_shift = true;
+ } else if (curr_amount >= total_target) {
+ // Success, adding more weight cannot be better: SHIFT
+ should_shift = true;
+ if (curr_weight < best_selection_weight || (curr_weight == best_selection_weight && curr_amount < best_selection_amount)) {
+ // New lowest weight, or same weight with fewer funds tied up
+ best_selection = curr_selection;
+ best_selection_weight = curr_weight;
+ best_selection_amount = curr_amount;
+ }
+ }
+
+ if (curr_try >= TOTAL_TRIES) {
+ // Solution is not guaranteed to be optimal if `curr_try` hit TOTAL_TRIES
+ break;
+ }
+
+ if (next_utxo == utxo_pool.size()) {
+ // Last added UTXO was end of UTXO pool, nothing left to add on inclusion or omission branch: CUT
+ should_cut = true;
+ }
+
+ if (should_cut) {
+ // Neither adding to the current selection nor exploring the omission branch of the last selected UTXO can
+ // find any solutions. Redirect to exploring the Omission branch of the penultimate selected UTXO (i.e.
+ // set `next_utxo` to one after the penultimate selected, then deselect the last two selected UTXOs)
+ should_cut = false;
+ deselect_last();
+ should_shift = true;
+ }
+
+ if (should_shift) {
+ // Set `next_utxo` to one after last selected, then deselect last selected UTXO
+ if (curr_selection.empty()) {
+ // Exhausted search space before running into attempt limit
+ break;
+ }
+ next_utxo = curr_selection.back() + 1;
+ deselect_last();
+ should_shift = false;
+ }
+ }
+
+ result.SetSelectionsEvaluated(curr_try);
+
+ if (best_selection.empty()) {
+ return max_tx_weight_exceeded ? ErrorMaxWeightExceeded() : util::Error();
+ }
+
+ for (const size_t& i : best_selection) {
+ result.AddInput(utxo_pool[i]);
+ }
+
+ return result;
+}
+
class MinOutputGroupComparator
{
public:
@@ -514,6 +794,16 @@ void SelectionResult::ComputeAndSetWaste(const CAmount min_viable_change, const
}
}
+void SelectionResult::SetSelectionsEvaluated(size_t attempts)
+{
+ m_selections_evaluated = attempts;
+}
+
+size_t SelectionResult::GetSelectionsEvaluated() const
+{
+ return m_selections_evaluated;
+}
+
CAmount SelectionResult::GetWaste() const
{
return *Assert(m_waste);
@@ -607,6 +897,7 @@ std::string GetAlgorithmName(const SelectionAlgorithm algo)
case SelectionAlgorithm::BNB: return "bnb";
case SelectionAlgorithm::KNAPSACK: return "knapsack";
case SelectionAlgorithm::SRD: return "srd";
+ case SelectionAlgorithm::CG: return "cg";
case SelectionAlgorithm::MANUAL: return "manual";
// No default case to allow for compiler to warn
}