package autopilot import ( prand "math/rand" "net" "time" "github.com/btcsuite/btcd/btcec" "github.com/btcsuite/btcutil" ) // ConstrainedPrefAttachment is an implementation of the AttachmentHeuristic // interface that implement a constrained non-linear preferential attachment // heuristic. This means that given a threshold to allocate to automatic // channel establishment, the heuristic will attempt to favor connecting to // nodes which already have a set amount of links, selected by sampling from a // power law distribution. The attachment is non-linear in that it favors // nodes with a higher in-degree but less so that regular linear preferential // attachment. As a result, this creates smaller and less clusters than regular // linear preferential attachment. // // TODO(roasbeef): BA, with k=-3 type ConstrainedPrefAttachment struct { constraints *HeuristicConstraints } // NewConstrainedPrefAttachment creates a new instance of a // ConstrainedPrefAttachment heuristics given bounds on allowed channel sizes, // and an allocation amount which is interpreted as a percentage of funds that // is to be committed to channels at all times. func NewConstrainedPrefAttachment( cfg *HeuristicConstraints) *ConstrainedPrefAttachment { prand.Seed(time.Now().Unix()) return &ConstrainedPrefAttachment{ constraints: cfg, } } // A compile time assertion to ensure ConstrainedPrefAttachment meets the // AttachmentHeuristic interface. var _ AttachmentHeuristic = (*ConstrainedPrefAttachment)(nil) // NeedMoreChans is a predicate that should return true if, given the passed // parameters, and its internal state, more channels should be opened within // the channel graph. If the heuristic decides that we do indeed need more // channels, then the second argument returned will represent the amount of // additional funds to be used towards creating channels. // // NOTE: This is a part of the AttachmentHeuristic interface. func (p *ConstrainedPrefAttachment) NeedMoreChans(channels []Channel, funds btcutil.Amount) (btcutil.Amount, uint32, bool) { // We'll try to open more channels as long as the constraints allow it. availableFunds, availableChans := p.constraints.availableChans( channels, funds, ) return availableFunds, availableChans, availableChans > 0 } // NodeID is a simple type that holds an EC public key serialized in compressed // format. type NodeID [33]byte // NewNodeID creates a new nodeID from a passed public key. func NewNodeID(pub *btcec.PublicKey) NodeID { var n NodeID copy(n[:], pub.SerializeCompressed()) return n } // NodeScores is a method that given the current channel graph, current set of // local channels and funds available, scores the given nodes according the the // preference of opening a channel with them. // // The heuristic employed by this method is one that attempts to promote a // scale-free network globally, via local attachment preferences for new nodes // joining the network with an amount of available funds to be allocated to // channels. Specifically, we consider the degree of each node (and the flow // in/out of the node available via its open channels) and utilize the // Barabási–Albert model to drive our recommended attachment heuristics. If // implemented globally for each new participant, this results in a channel // graph that is scale-free and follows a power law distribution with k=-3. // // The returned scores will be in the range [0.0, 1.0], where higher scores are // given to nodes already having high connectivity in the graph. // // NOTE: This is a part of the AttachmentHeuristic interface. func (p *ConstrainedPrefAttachment) NodeScores(g ChannelGraph, chans []Channel, fundsAvailable btcutil.Amount, nodes map[NodeID]struct{}) ( map[NodeID]*AttachmentDirective, error) { // Count the number of channels in the graph. We'll also count the // number of channels as we go for the nodes we are interested in, and // record their addresses found in the db. var graphChans int nodeChanNum := make(map[NodeID]int) addresses := make(map[NodeID][]net.Addr) if err := g.ForEachNode(func(n Node) error { var nodeChans int err := n.ForEachChannel(func(_ ChannelEdge) error { nodeChans++ graphChans++ return nil }) if err != nil { return err } // If this node is not among our nodes to score, we can return // early. nID := NodeID(n.PubKey()) if _, ok := nodes[nID]; !ok { return nil } // Otherwise we'll record the number of channels, and also // populate the address in our channel candidates map. nodeChanNum[nID] = nodeChans addresses[nID] = n.Addrs() return nil }); err != nil { return nil, err } // If there are no channels in the graph we cannot determine any // preferences, so we return, indicating all candidates get a score of // zero. if graphChans == 0 { return nil, nil } existingPeers := make(map[NodeID]struct{}) for _, c := range chans { existingPeers[c.Node] = struct{}{} } // For each node in the set of nodes, count their fraction of channels // in the graph, and use that as the score. candidates := make(map[NodeID]*AttachmentDirective) for nID, nodeChans := range nodeChanNum { // As channel size we'll use the maximum channel size available. chanSize := p.constraints.MaxChanSize if fundsAvailable-chanSize < 0 { chanSize = fundsAvailable } _, ok := existingPeers[nID] switch { // If the node is among or existing channel peers, we don't // need another channel. case ok: continue // If the amount is too small, we don't want to attempt opening // another channel. case chanSize == 0 || chanSize < p.constraints.MinChanSize: continue } // Otherwise we score the node according to its fraction of // channels in the graph. score := float64(nodeChans) / float64(graphChans) candidates[nID] = &AttachmentDirective{ NodeID: nID, ChanAmt: chanSize, Score: score, } } return candidates, nil }