306c4aef8e
This commit introduces the initial implementation of the autopilot mode. Autopilot is new mode within lnd that enables automatic channel management. This means that if enabled lnd will attempt to automatically manage channels according to a set of heuristic defined within the main configuration for autopilot.Agent instance. The autopilot.Agent implements a simple closed control loop. It takes in external signals such as wallet balance updates, new open channel, and channels that are now closed the updates its internal state. With each external trigger it will consult the registered AttachmentHeuristic to decide: if it needs to open any more channels, and if so how much it should use to open the channels, ultimately returning a set of recommended AttachmentDirectives. The autopilot.Agent loop will then take those attempt to establish connection, and go back in waiting for a new external signal. With this first implementation the default heuristic is the ConstrainedPrefAttachment implementation of AttachmentHeuristic. Given a min and max channel size, a limit on the number of channels, and the percentage of wallet funds to allocate to channels, it will attempt to execute a heuristic drive by the Barabási–Albert model model in order to attempt to drive the global graph towards a scale free topology. This is commit implements a foundational layer for future simulations, optimization, and additional heuristics.
272 lines
9.4 KiB
Go
272 lines
9.4 KiB
Go
package autopilot
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import (
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"fmt"
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prand "math/rand"
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"time"
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"github.com/roasbeef/btcd/btcec"
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"github.com/roasbeef/btcutil"
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)
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// ConstrainedPrefAttachment is an implementation of the AttachmentHeuristic
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// interface that implement a constrained non-linear preferential attachment
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// heuristic. This means that given a threshold to allocate to automatic
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// channel establishment, the heuristic will attempt to favor connecting to
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// nodes which already have a set amount of links, selected by sampling from a
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// power law distribution. The attachment ins non-linear in that it favors
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// nodes with a higher in-degree but less so that regular linear preferential
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// attachment. As a result, this creates smaller and less clusters than regular
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// linear preferential attachment.
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//
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// TODO(roasbeef): BA, with k=-3
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type ConstrainedPrefAttachment struct {
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minChanSize btcutil.Amount
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maxChanSize btcutil.Amount
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chanLimit uint16
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threshold float64
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}
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// NewPrefAttchment creates a new instance of a ConstrainedPrefAttachment
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// heuristics given bounds on allowed channel sizes, and an allocation amount
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// which is interpreted as a percentage of funds that is to be committed to
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// channels at all times.
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func NewConstrainedPrefAttachment(minChanSize, maxChanSize btcutil.Amount,
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chanLimit uint16, allocation float64) *ConstrainedPrefAttachment {
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prand.Seed(time.Now().Unix())
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return &ConstrainedPrefAttachment{
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minChanSize: minChanSize,
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chanLimit: chanLimit,
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maxChanSize: maxChanSize,
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threshold: allocation,
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}
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}
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// A compile time assertion to ensure ConstrainedPrefAttachment meets the
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// AttachmentHeuristic interface.
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var _ AttachmentHeuristic = (*ConstrainedPrefAttachment)(nil)
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// NeedMoreChans is a predicate that should return true if, given the passed
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// parameters, and its internal state, more channels should be opened within
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// the channel graph. If the heuristic decides that we do indeed need more
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// channels, then the second argument returned will represent the amount of
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// additional funds to be used towards creating channels.
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//
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// NOTE: This is a part of the AttachmentHeuristic interface.
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func (p *ConstrainedPrefAttachment) NeedMoreChans(channels []Channel,
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funds btcutil.Amount) (btcutil.Amount, bool) {
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// If we're already over our maximum allowed number of channels, then
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// we'll instruct the controller not to create any more channels.
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if len(channels) >= int(p.chanLimit) {
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return 0, false
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}
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// First, we'll tally up the total amount of funds that are currently
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// present within the set of active channels.
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var totalChanAllocation btcutil.Amount
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for _, channel := range channels {
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totalChanAllocation += channel.Capacity
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}
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// With this value known, we'll now compute the total amount of fund
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// allocated across regular utxo's and channel utxo's.
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totalFunds := funds + totalChanAllocation
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// Once the total amount has been computed, we then calculate the
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// fraction of funds currently allocated to channels.
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fundsFraction := float64(totalChanAllocation) / float64(totalFunds)
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// If this fraction is below our threshold, then we'll return true, to
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// indicate the controller should call Select to obtain a candidate set
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// of channels to attempt to open.
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needMore := fundsFraction < p.threshold
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if !needMore {
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return 0, false
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}
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// Now that we know we need more funds, we'll compute the amount of
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// additional funds we should allocate towards channels.
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targetAllocation := btcutil.Amount(float64(totalFunds) * p.threshold)
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fundsAvailable := targetAllocation - totalChanAllocation
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return fundsAvailable, true
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}
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// nodeID is a simple type that holds a EC public key serialized in compressed
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// format.
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type NodeID [33]byte
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// NewNodeID creates a new nodeID from a passed public key.
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func NewNodeID(pub *btcec.PublicKey) NodeID {
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var n NodeID
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copy(n[:], pub.SerializeCompressed())
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return n
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}
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// Select returns a candidate set of attachment directives that should be
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// executed based on the current internal state, the state of the channel
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// graph, the set of nodes we should exclude, and the amount of funds
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// available. The heuristic employed by this method is one that attempts to
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// promote a scale-free network globally, via local attachment preferences for
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// new nodes joining the network with an amount of available funds to be
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// allocated to channels. Specifically, we consider the degree of each node
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// (and the flow in/out of the node available via its open channels) and
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// utilize the Barabási–Albert model to drive our recommended attachment
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// heuristics. If implemented globally for each new participant, this results
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// in a channel graph that is scale-free and follows a power law distribution
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// with k=-3.
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//
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// NOTE: This is a part of the AttachmentHeuristic interface.
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func (p *ConstrainedPrefAttachment) Select(self *btcec.PublicKey, g ChannelGraph,
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fundsAvailable btcutil.Amount, skipNodes map[NodeID]struct{}) ([]AttachmentDirective, error) {
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// TODO(roasbeef): rename?
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var directives []AttachmentDirective
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if fundsAvailable < p.minChanSize {
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return directives, nil
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}
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// We'll continue our attachment loop until we've exhausted the current
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// amount of available funds.
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visited := make(map[NodeID]struct{})
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for i := uint16(0); i < p.chanLimit; i++ {
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// selectionSlice will be used to randomly select a node
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// according to a power law distribution. For each connected
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// edge, we'll add an instance of the node to this slice. Thus,
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// for a given node, the probability that we'll attach to it
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// is: k_i / sum(k_j), where k_i is the degree of the target
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// node, and k_j is the degree of all other nodes i != j. This
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// implements the classic Barabási–Albert model for
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// preferential attachment.
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var selectionSlice []Node
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// For each node, and each channel that the node has, we'll add
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// an instance of that node to the selection slice above.
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// This'll slice where the frequency of each node is equivalent
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// to the number of channels that connect to it.
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//
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// TODO(roasbeef): add noise to make adversarially resistant?
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if err := g.ForEachNode(func(node Node) error {
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nID := NewNodeID(node.PubKey())
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// Once a node has already been attached to, we'll
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// ensure that it isn't factored into any further
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// decisions within this round.
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if _, ok := visited[nID]; ok {
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return nil
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}
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// If we come across ourselves, them we'll continue in
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// order to avoid attempting to make a channel with
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// ourselves.
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if node.PubKey().IsEqual(self) {
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return nil
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}
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// Additionally, if this node is in the backlist, then
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// we'll skip it.
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if _, ok := skipNodes[nID]; ok {
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return nil
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}
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// For initial bootstrap purposes, if a node doesn't
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// have any channels, then we'll ensure that it has at
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// least one item in the selection slice.
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//
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// TODO(roasbeef): make conditional?
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selectionSlice = append(selectionSlice, node)
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// For each active channel the node has, we'll add an
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// additional channel to the selection slice to
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// increase their weight.
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if err := node.ForEachChannel(func(channel ChannelEdge) error {
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selectionSlice = append(selectionSlice, node)
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return nil
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}); err != nil {
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return err
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}
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return nil
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}); err != nil {
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return nil, err
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}
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// If no nodes at all were accumulated, then we'll exit early
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// as there are no eligible candidates.
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if len(selectionSlice) == 0 {
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break
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}
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// Given our selection slice, we'll now generate a random index
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// into this slice. The node we select will be recommended by
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// us to create a channel to.
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selectedIndex := prand.Int31n(int32(len(selectionSlice)))
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selectedNode := selectionSlice[selectedIndex]
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// TODO(roasbeef): cap on num channels to same participant?
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// With the node selected, we'll add this (node, amount) tuple
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// to out set of recommended directives.
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pub := selectedNode.PubKey()
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directives = append(directives, AttachmentDirective{
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// TODO(roasbeef): need curve?
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PeerKey: &btcec.PublicKey{
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X: pub.X,
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Y: pub.Y,
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},
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Addrs: selectedNode.Addrs(),
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})
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// With the node selected, we'll add it to the set of visited
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// nodes to avoid attaching to it again.
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visited[NewNodeID(selectedNode.PubKey())] = struct{}{}
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}
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numSelectedNodes := int64(len(directives))
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switch {
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// If we have enough available funds to distribute the maximum channel
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// size for each of the selected peers to attach to, then we'll
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// allocate the maximum amount to each peer.
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case int64(fundsAvailable) >= numSelectedNodes*int64(p.maxChanSize):
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for i := 0; i < int(numSelectedNodes); i++ {
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directives[i].ChanAmt = p.maxChanSize
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}
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return directives, nil
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// Otherwise, we'll greedily allocate our funds to the channels
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// successively until we run out of available funds, or can't create a
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// channel above the min channel size.
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case int64(fundsAvailable) < numSelectedNodes*int64(p.maxChanSize):
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i := 0
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for fundsAvailable > p.minChanSize {
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// We'll attempt to allocate the max channel size
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// initially. If we don't have enough funds to do this,
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// then we'll allocate the remainder of the funds
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// available to the channel.
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delta := p.maxChanSize
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if fundsAvailable-delta < 0 {
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delta = fundsAvailable
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}
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directives[i].ChanAmt = delta
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fundsAvailable -= delta
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i++
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}
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// We'll slice the initial set of directives to properly
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// reflect the amount of funds we were able to allocate.
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return directives[:i:i], nil
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default:
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return nil, fmt.Errorf("err")
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}
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}
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