go-ethereum/les/utils/weighted_select.go
Felföldi Zsolt b4a2681120
les, les/lespay: implement new server pool (#20758)
This PR reimplements the light client server pool. It is also a first step
to move certain logic into a new lespay package. This package will contain
the implementation of the lespay token sale functions, the token buying and
selling logic and other components related to peer selection/prioritization
and service quality evaluation. Over the long term this package will be
reusable for incentivizing future protocols.

Since the LES peer logic is now based on enode.Iterator, it can now use
DNS-based fallback discovery to find servers.

This document describes the function of the new components:
https://gist.github.com/zsfelfoldi/3c7ace895234b7b345ab4f71dab102d4
2020-05-22 13:46:34 +02:00

173 lines
5.1 KiB
Go

// Copyright 2016 The go-ethereum Authors
// This file is part of the go-ethereum library.
//
// The go-ethereum library is free software: you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// The go-ethereum library is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with the go-ethereum library. If not, see <http://www.gnu.org/licenses/>.
package utils
import (
"math/rand"
)
type (
// WeightedRandomSelect is capable of weighted random selection from a set of items
WeightedRandomSelect struct {
root *wrsNode
idx map[WrsItem]int
wfn WeightFn
}
WrsItem interface{}
WeightFn func(interface{}) uint64
)
// NewWeightedRandomSelect returns a new WeightedRandomSelect structure
func NewWeightedRandomSelect(wfn WeightFn) *WeightedRandomSelect {
return &WeightedRandomSelect{root: &wrsNode{maxItems: wrsBranches}, idx: make(map[WrsItem]int), wfn: wfn}
}
// Update updates an item's weight, adds it if it was non-existent or removes it if
// the new weight is zero. Note that explicitly updating decreasing weights is not necessary.
func (w *WeightedRandomSelect) Update(item WrsItem) {
w.setWeight(item, w.wfn(item))
}
// Remove removes an item from the set
func (w *WeightedRandomSelect) Remove(item WrsItem) {
w.setWeight(item, 0)
}
// IsEmpty returns true if the set is empty
func (w *WeightedRandomSelect) IsEmpty() bool {
return w.root.sumWeight == 0
}
// setWeight sets an item's weight to a specific value (removes it if zero)
func (w *WeightedRandomSelect) setWeight(item WrsItem, weight uint64) {
idx, ok := w.idx[item]
if ok {
w.root.setWeight(idx, weight)
if weight == 0 {
delete(w.idx, item)
}
} else {
if weight != 0 {
if w.root.itemCnt == w.root.maxItems {
// add a new level
newRoot := &wrsNode{sumWeight: w.root.sumWeight, itemCnt: w.root.itemCnt, level: w.root.level + 1, maxItems: w.root.maxItems * wrsBranches}
newRoot.items[0] = w.root
newRoot.weights[0] = w.root.sumWeight
w.root = newRoot
}
w.idx[item] = w.root.insert(item, weight)
}
}
}
// Choose randomly selects an item from the set, with a chance proportional to its
// current weight. If the weight of the chosen element has been decreased since the
// last stored value, returns it with a newWeight/oldWeight chance, otherwise just
// updates its weight and selects another one
func (w *WeightedRandomSelect) Choose() WrsItem {
for {
if w.root.sumWeight == 0 {
return nil
}
val := uint64(rand.Int63n(int64(w.root.sumWeight)))
choice, lastWeight := w.root.choose(val)
weight := w.wfn(choice)
if weight != lastWeight {
w.setWeight(choice, weight)
}
if weight >= lastWeight || uint64(rand.Int63n(int64(lastWeight))) < weight {
return choice
}
}
}
const wrsBranches = 8 // max number of branches in the wrsNode tree
// wrsNode is a node of a tree structure that can store WrsItems or further wrsNodes.
type wrsNode struct {
items [wrsBranches]interface{}
weights [wrsBranches]uint64
sumWeight uint64
level, itemCnt, maxItems int
}
// insert recursively inserts a new item to the tree and returns the item index
func (n *wrsNode) insert(item WrsItem, weight uint64) int {
branch := 0
for n.items[branch] != nil && (n.level == 0 || n.items[branch].(*wrsNode).itemCnt == n.items[branch].(*wrsNode).maxItems) {
branch++
if branch == wrsBranches {
panic(nil)
}
}
n.itemCnt++
n.sumWeight += weight
n.weights[branch] += weight
if n.level == 0 {
n.items[branch] = item
return branch
}
var subNode *wrsNode
if n.items[branch] == nil {
subNode = &wrsNode{maxItems: n.maxItems / wrsBranches, level: n.level - 1}
n.items[branch] = subNode
} else {
subNode = n.items[branch].(*wrsNode)
}
subIdx := subNode.insert(item, weight)
return subNode.maxItems*branch + subIdx
}
// setWeight updates the weight of a certain item (which should exist) and returns
// the change of the last weight value stored in the tree
func (n *wrsNode) setWeight(idx int, weight uint64) uint64 {
if n.level == 0 {
oldWeight := n.weights[idx]
n.weights[idx] = weight
diff := weight - oldWeight
n.sumWeight += diff
if weight == 0 {
n.items[idx] = nil
n.itemCnt--
}
return diff
}
branchItems := n.maxItems / wrsBranches
branch := idx / branchItems
diff := n.items[branch].(*wrsNode).setWeight(idx-branch*branchItems, weight)
n.weights[branch] += diff
n.sumWeight += diff
if weight == 0 {
n.itemCnt--
}
return diff
}
// choose recursively selects an item from the tree and returns it along with its weight
func (n *wrsNode) choose(val uint64) (WrsItem, uint64) {
for i, w := range n.weights {
if val < w {
if n.level == 0 {
return n.items[i].(WrsItem), n.weights[i]
}
return n.items[i].(*wrsNode).choose(val)
}
val -= w
}
panic(nil)
}