plugeth/p2p/discover/table.go

281 lines
7.4 KiB
Go

// Package discover implements the Node Discovery Protocol.
//
// The Node Discovery protocol provides a way to find RLPx nodes that
// can be connected to. It uses a Kademlia-like protocol to maintain a
// distributed database of the IDs and endpoints of all listening
// nodes.
package discover
import (
"net"
"sort"
"sync"
"time"
)
const (
alpha = 3 // Kademlia concurrency factor
bucketSize = 16 // Kademlia bucket size
nBuckets = nodeIDBits + 1 // Number of buckets
)
type Table struct {
mutex sync.Mutex // protects buckets, their content, and nursery
buckets [nBuckets]*bucket // index of known nodes by distance
nursery []*Node // bootstrap nodes
net transport
self *Node // metadata of the local node
}
// transport is implemented by the UDP transport.
// it is an interface so we can test without opening lots of UDP
// sockets and without generating a private key.
type transport interface {
ping(*Node) error
findnode(e *Node, target NodeID) ([]*Node, error)
close()
}
// bucket contains nodes, ordered by their last activity.
type bucket struct {
lastLookup time.Time
entries []*Node
}
func newTable(t transport, ourID NodeID, ourAddr *net.UDPAddr) *Table {
tab := &Table{net: t, self: newNode(ourID, ourAddr)}
for i := range tab.buckets {
tab.buckets[i] = new(bucket)
}
return tab
}
// Self returns the local node.
func (tab *Table) Self() *Node {
return tab.self
}
// Close terminates the network listener.
func (tab *Table) Close() {
tab.net.close()
}
// Bootstrap sets the bootstrap nodes. These nodes are used to connect
// to the network if the table is empty. Bootstrap will also attempt to
// fill the table by performing random lookup operations on the
// network.
func (tab *Table) Bootstrap(nodes []*Node) {
tab.mutex.Lock()
// TODO: maybe filter nodes with bad fields (nil, etc.) to avoid strange crashes
tab.nursery = make([]*Node, 0, len(nodes))
for _, n := range nodes {
cpy := *n
tab.nursery = append(tab.nursery, &cpy)
}
tab.mutex.Unlock()
tab.refresh()
}
// Lookup performs a network search for nodes close
// to the given target. It approaches the target by querying
// nodes that are closer to it on each iteration.
func (tab *Table) Lookup(target NodeID) []*Node {
var (
asked = make(map[NodeID]bool)
seen = make(map[NodeID]bool)
reply = make(chan []*Node, alpha)
pendingQueries = 0
)
// don't query further if we hit the target or ourself.
// unlikely to happen often in practice.
asked[target] = true
asked[tab.self.ID] = true
tab.mutex.Lock()
// update last lookup stamp (for refresh logic)
tab.buckets[logdist(tab.self.ID, target)].lastLookup = time.Now()
// generate initial result set
result := tab.closest(target, bucketSize)
tab.mutex.Unlock()
for {
// ask the alpha closest nodes that we haven't asked yet
for i := 0; i < len(result.entries) && pendingQueries < alpha; i++ {
n := result.entries[i]
if !asked[n.ID] {
asked[n.ID] = true
pendingQueries++
go func() {
result, _ := tab.net.findnode(n, target)
reply <- result
}()
}
}
if pendingQueries == 0 {
// we have asked all closest nodes, stop the search
break
}
// wait for the next reply
for _, n := range <-reply {
cn := n
if !seen[n.ID] {
seen[n.ID] = true
result.push(cn, bucketSize)
}
}
pendingQueries--
}
return result.entries
}
// refresh performs a lookup for a random target to keep buckets full.
func (tab *Table) refresh() {
ld := -1 // logdist of chosen bucket
tab.mutex.Lock()
for i, b := range tab.buckets {
if i > 0 && b.lastLookup.Before(time.Now().Add(-1*time.Hour)) {
ld = i
break
}
}
tab.mutex.Unlock()
result := tab.Lookup(randomID(tab.self.ID, ld))
if len(result) == 0 {
// bootstrap the table with a self lookup
tab.mutex.Lock()
tab.add(tab.nursery)
tab.mutex.Unlock()
tab.Lookup(tab.self.ID)
// TODO: the Kademlia paper says that we're supposed to perform
// random lookups in all buckets further away than our closest neighbor.
}
}
// closest returns the n nodes in the table that are closest to the
// given id. The caller must hold tab.mutex.
func (tab *Table) closest(target NodeID, nresults int) *nodesByDistance {
// This is a very wasteful way to find the closest nodes but
// obviously correct. I believe that tree-based buckets would make
// this easier to implement efficiently.
close := &nodesByDistance{target: target}
for _, b := range tab.buckets {
for _, n := range b.entries {
close.push(n, nresults)
}
}
return close
}
func (tab *Table) len() (n int) {
for _, b := range tab.buckets {
n += len(b.entries)
}
return n
}
// bumpOrAdd updates the activity timestamp for the given node and
// attempts to insert the node into a bucket. The returned Node might
// not be part of the table. The caller must hold tab.mutex.
func (tab *Table) bumpOrAdd(node NodeID, from *net.UDPAddr) (n *Node) {
b := tab.buckets[logdist(tab.self.ID, node)]
if n = b.bump(node); n == nil {
n = newNode(node, from)
if len(b.entries) == bucketSize {
tab.pingReplace(n, b)
} else {
b.entries = append(b.entries, n)
}
}
return n
}
func (tab *Table) pingReplace(n *Node, b *bucket) {
old := b.entries[bucketSize-1]
go func() {
if err := tab.net.ping(old); err == nil {
// it responded, we don't need to replace it.
return
}
// it didn't respond, replace the node if it is still the oldest node.
tab.mutex.Lock()
if len(b.entries) > 0 && b.entries[len(b.entries)-1] == old {
// slide down other entries and put the new one in front.
// TODO: insert in correct position to keep the order
copy(b.entries[1:], b.entries)
b.entries[0] = n
}
tab.mutex.Unlock()
}()
}
// bump updates the activity timestamp for the given node.
// The caller must hold tab.mutex.
func (tab *Table) bump(node NodeID) {
tab.buckets[logdist(tab.self.ID, node)].bump(node)
}
// add puts the entries into the table if their corresponding
// bucket is not full. The caller must hold tab.mutex.
func (tab *Table) add(entries []*Node) {
outer:
for _, n := range entries {
if n == nil || n.ID == tab.self.ID {
// skip bad entries. The RLP decoder returns nil for empty
// input lists.
continue
}
bucket := tab.buckets[logdist(tab.self.ID, n.ID)]
for i := range bucket.entries {
if bucket.entries[i].ID == n.ID {
// already in bucket
continue outer
}
}
if len(bucket.entries) < bucketSize {
bucket.entries = append(bucket.entries, n)
}
}
}
func (b *bucket) bump(id NodeID) *Node {
for i, n := range b.entries {
if n.ID == id {
n.active = time.Now()
// move it to the front
copy(b.entries[1:], b.entries[:i+1])
b.entries[0] = n
return n
}
}
return nil
}
// nodesByDistance is a list of nodes, ordered by
// distance to target.
type nodesByDistance struct {
entries []*Node
target NodeID
}
// push adds the given node to the list, keeping the total size below maxElems.
func (h *nodesByDistance) push(n *Node, maxElems int) {
ix := sort.Search(len(h.entries), func(i int) bool {
return distcmp(h.target, h.entries[i].ID, n.ID) > 0
})
if len(h.entries) < maxElems {
h.entries = append(h.entries, n)
}
if ix == len(h.entries) {
// farther away than all nodes we already have.
// if there was room for it, the node is now the last element.
} else {
// slide existing entries down to make room
// this will overwrite the entry we just appended.
copy(h.entries[ix+1:], h.entries[ix:])
h.entries[ix] = n
}
}