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routing.go
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routing.go
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package dht
import (
l4g "code.google.com/p/log4go"
)
// DHT routing using a binary tree and no buckets.
//
// Nodes have ids of 20-bytes. When looking up an infohash for itself or for a
// remote host, the nodes have to look in its routing table for the closest
// nodes and return them.
//
// The distance between a node and an infohash is the XOR of the respective
// strings. This means that 'sorting' nodes only makes sense with an infohash
// as the pivot. You can't pre-sort nodes in any meaningful way.
//
// Most bittorrent/kademlia DHT implementations use a mix of bit-by-bit
// comparison with the usage of buckets. That works very well. But I wanted to
// try something different, that doesn't use buckets. Buckets have a single id
// and one calculates the distance based on that, speeding up lookups.
//
// I decided to lay out the routing table in a binary tree instead, which is
// more intuitive. At the moment, the implementation is a real tree, not a
// free-list, but it's performing well.
//
// All nodes are inserted in the binary tree, with a fixed height of 160 (20
// bytes). To lookup an infohash, I do an inorder traversal using the infohash
// bit for each level.
//
// In most cases the lookup reaches the bottom of the tree without hitting the
// target infohash, since in the vast majority of the cases it's not in my
// routing table. Then I simply continue the in-order traversal (but then to
// the 'left') and return after I collect the 8 closest nodes.
//
// To speed things up, I keep the tree as short as possible. The path to each
// node is compressed and later uncompressed if a collision happens when
// inserting another node.
//
// I don't know how slow the overall algorithm is compared to a implementation
// that uses buckets, but for what is worth, the routing table lookups don't
// even show on the CPU profiling anymore.
import (
"time"
)
type nTree struct {
zero, one *nTree
value *remoteNode
}
const (
// Each query returns up to this number of nodes.
kNodes = 8
// Search a node again after some time.
searchRetryPeriod = 15 * time.Second
// Consider a node stale if it has more than this number of oustanding
// queries from us.
maxNodePendingQueries = 5
)
// recursive version of node insertion.
func (n *nTree) insert(newNode *remoteNode) {
n.put(newNode, 0)
}
func (n *nTree) branchOut(n1, n2 *remoteNode, i int) {
// Since they are branching out it's guaranteed that no other nodes
// exist below this branch currently, so just create the respective
// nodes until their respective bits are different.
chr := byte(n1.id[i/8])
bitPos := byte(i % 8)
bit := (chr << bitPos) & 128
chr2 := byte(n2.id[i/8])
bitPos2 := byte(i % 8)
bit2 := (chr2 << bitPos2) & 128
if bit != bit2 {
n.put(n1, i)
n.put(n2, i)
return
}
// Identical bits.
if bit != 0 {
n.one = &nTree{}
n.one.branchOut(n1, n2, i+1)
} else {
n.zero = &nTree{}
n.zero.branchOut(n1, n2, i+1)
}
}
func (n *nTree) put(newNode *remoteNode, i int) {
if i >= len(newNode.id)*8 {
// Replaces the existing value, if any.
n.value = newNode
return
}
if n.value != nil {
if n.value.id == newNode.id {
// Replace existing compressed value.
n.value = newNode
return
}
// Compression collision. Branch them out.
old := n.value
n.value = nil
n.branchOut(newNode, old, i)
return
}
chr := byte(newNode.id[i/8])
bit := byte(i % 8)
if (chr<<bit)&128 != 0 {
if n.one == nil {
n.one = &nTree{value: newNode}
return
}
n.one.put(newNode, i+1)
} else {
if n.zero == nil {
n.zero = &nTree{value: newNode}
return
}
n.zero.put(newNode, i+1)
}
}
func (n *nTree) lookup(id InfoHash) []*remoteNode {
ret := make([]*remoteNode, 0, kNodes)
if n == nil || id == "" {
return nil
}
return n.traverse(id, 0, ret, false)
}
func (n *nTree) lookupFiltered(id InfoHash) []*remoteNode {
ret := make([]*remoteNode, 0, kNodes)
if n == nil || id == "" {
return nil
}
return n.traverse(id, 0, ret, true)
}
func (n *nTree) traverse(id InfoHash, i int, ret []*remoteNode, filter bool) []*remoteNode {
if n == nil {
return ret
}
if n.value != nil {
if !filter || n.isOK(id) {
return append(ret, n.value)
}
}
if i >= len(id)*8 {
return ret
}
if len(ret) >= kNodes {
return ret
}
chr := byte(id[i/8])
bit := byte(i % 8)
// This is not needed, but it's clearer.
var left, right *nTree
if (chr<<bit)&128 != 0 {
left = n.one
right = n.zero
} else {
left = n.zero
right = n.one
}
ret = left.traverse(id, i+1, ret, filter)
if len(ret) >= kNodes {
return ret
}
return right.traverse(id, i+1, ret, filter)
}
// cut goes down the tree and deletes the children nodes if all their leaves
// became empty.
func (n *nTree) cut(id InfoHash, i int) (cutMe bool) {
if n == nil {
return true
}
if i >= len(id)*8 {
return true
}
chr := byte(id[i/8])
bit := byte(i % 8)
if (chr<<bit)&128 != 0 {
if n.one.cut(id, i+1) {
n.one = nil
if n.zero == nil {
return true
}
}
} else {
if n.zero.cut(id, i+1) {
n.zero = nil
if n.one == nil {
return true
}
}
}
return false
}
func (n *nTree) isOK(ih InfoHash) bool {
if n.value == nil || n.value.id == "" {
return false
}
r := n.value
if len(r.pendingQueries) > maxNodePendingQueries {
// debug.Println("DHT: Skipping because there are too many queries pending for this dude.")
// debug.Println("DHT: This shouldn't happen because we should have stopped trying already. Might be a BUG.")
return false
}
recent := r.wasContactedRecently(ih)
l4g.Trace("wasContactedRecently for ih=%x in node %x@%v returned %v", ih, r.id, r.address, recent)
if recent {
return false
}
return true
}
func commonBits(s1, s2 string) int {
// copied from jch's dht.cc.
id1, id2 := []byte(s1), []byte(s2)
i := 0
for ; i < 20; i++ {
if id1[i] != id2[i] {
break
}
}
if i == 20 {
return 160
}
xor := id1[i] ^ id2[i]
j := 0
for (xor & 0x80) == 0 {
xor <<= 1
j++
}
return 8*i + j
}
// Calculates the distance between two hashes. In DHT/Kademlia, "distance" is
// the XOR of the torrent infohash and the peer node ID. This is slower than
// necessary. Should only be used for displaying friendly messages.
func hashDistance(id1 InfoHash, id2 InfoHash) (distance string) {
d := make([]byte, len(id1))
if len(id1) != len(id2) {
return ""
} else {
for i := 0; i < len(id1); i++ {
d[i] = id1[i] ^ id2[i]
}
return string(d)
}
return ""
}