go-pulse/les/costtracker.go

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les, les/flowcontrol: improved request serving and flow control (#18230) This change - implements concurrent LES request serving even for a single peer. - replaces the request cost estimation method with a cost table based on benchmarks which gives much more consistent results. Until now the allowed number of light peers was just a guess which probably contributed a lot to the fluctuating quality of available service. Everything related to request cost is implemented in a single object, the 'cost tracker'. It uses a fixed cost table with a global 'correction factor'. Benchmark code is included and can be run at any time to adapt costs to low-level implementation changes. - reimplements flowcontrol.ClientManager in a cleaner and more efficient way, with added capabilities: There is now control over bandwidth, which allows using the flow control parameters for client prioritization. Target utilization over 100 percent is now supported to model concurrent request processing. Total serving bandwidth is reduced during block processing to prevent database contention. - implements an RPC API for the LES servers allowing server operators to assign priority bandwidth to certain clients and change prioritized status even while the client is connected. The new API is meant for cases where server operators charge for LES using an off-protocol mechanism. - adds a unit test for the new client manager. - adds an end-to-end test using the network simulator that tests bandwidth control functions through the new API.
2019-02-26 11:32:48 +00:00
// 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 detailct.
//
// 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 les
import (
"encoding/binary"
"math"
"sync"
"sync/atomic"
"time"
"github.com/ethereum/go-ethereum/common/mclock"
"github.com/ethereum/go-ethereum/eth"
"github.com/ethereum/go-ethereum/ethdb"
"github.com/ethereum/go-ethereum/les/flowcontrol"
"github.com/ethereum/go-ethereum/log"
)
const makeCostStats = false // make request cost statistics during operation
var (
// average request cost estimates based on serving time
reqAvgTimeCost = requestCostTable{
GetBlockHeadersMsg: {150000, 30000},
GetBlockBodiesMsg: {0, 700000},
GetReceiptsMsg: {0, 1000000},
GetCodeMsg: {0, 450000},
GetProofsV2Msg: {0, 600000},
GetHelperTrieProofsMsg: {0, 1000000},
SendTxV2Msg: {0, 450000},
GetTxStatusMsg: {0, 250000},
}
// maximum incoming message size estimates
reqMaxInSize = requestCostTable{
GetBlockHeadersMsg: {40, 0},
GetBlockBodiesMsg: {0, 40},
GetReceiptsMsg: {0, 40},
GetCodeMsg: {0, 80},
GetProofsV2Msg: {0, 80},
GetHelperTrieProofsMsg: {0, 20},
SendTxV2Msg: {0, 66000},
GetTxStatusMsg: {0, 50},
}
// maximum outgoing message size estimates
reqMaxOutSize = requestCostTable{
GetBlockHeadersMsg: {0, 556},
GetBlockBodiesMsg: {0, 100000},
GetReceiptsMsg: {0, 200000},
GetCodeMsg: {0, 50000},
GetProofsV2Msg: {0, 4000},
GetHelperTrieProofsMsg: {0, 4000},
SendTxV2Msg: {0, 100},
GetTxStatusMsg: {0, 100},
}
minBufLimit = uint64(50000000 * maxCostFactor) // minimum buffer limit allowed for a client
minCapacity = (minBufLimit-1)/bufLimitRatio + 1 // minimum capacity allowed for a client
)
const (
maxCostFactor = 2 // ratio of maximum and average cost estimates
gfInitWeight = time.Second * 10
gfMaxWeight = time.Hour
gfUsageThreshold = 0.5
gfUsageTC = time.Second
gfDbKey = "_globalCostFactor"
)
// costTracker is responsible for calculating costs and cost estimates on the
// server side. It continuously updates the global cost factor which is defined
// as the number of cost units per nanosecond of serving time in a single thread.
// It is based on statistics collected during serving requests in high-load periods
// and practically acts as a one-dimension request price scaling factor over the
// pre-defined cost estimate table. Instead of scaling the cost values, the real
// value of cost units is changed by applying the factor to the serving times. This
// is more convenient because the changes in the cost factor can be applied immediately
// without always notifying the clients about the changed cost tables.
type costTracker struct {
db ethdb.Database
stopCh chan chan struct{}
inSizeFactor, outSizeFactor float64
gf, utilTarget float64
gfUpdateCh chan gfUpdate
gfLock sync.RWMutex
totalRechargeCh chan uint64
stats map[uint64][]uint64
}
// newCostTracker creates a cost tracker and loads the cost factor statistics from the database
func newCostTracker(db ethdb.Database, config *eth.Config) *costTracker {
utilTarget := float64(config.LightServ) * flowcontrol.FixedPointMultiplier / 100
ct := &costTracker{
db: db,
stopCh: make(chan chan struct{}),
utilTarget: utilTarget,
}
if config.LightBandwidthIn > 0 {
ct.inSizeFactor = utilTarget / float64(config.LightBandwidthIn)
}
if config.LightBandwidthOut > 0 {
ct.outSizeFactor = utilTarget / float64(config.LightBandwidthOut)
}
if makeCostStats {
ct.stats = make(map[uint64][]uint64)
for code := range reqAvgTimeCost {
ct.stats[code] = make([]uint64, 10)
}
}
ct.gfLoop()
return ct
}
// stop stops the cost tracker and saves the cost factor statistics to the database
func (ct *costTracker) stop() {
stopCh := make(chan struct{})
ct.stopCh <- stopCh
<-stopCh
if makeCostStats {
ct.printStats()
}
}
// makeCostList returns upper cost estimates based on the hardcoded cost estimate
// tables and the optionally specified incoming/outgoing bandwidth limits
func (ct *costTracker) makeCostList() RequestCostList {
maxCost := func(avgTime, inSize, outSize uint64) uint64 {
globalFactor := ct.globalFactor()
cost := avgTime * maxCostFactor
inSizeCost := uint64(float64(inSize) * ct.inSizeFactor * globalFactor * maxCostFactor)
if inSizeCost > cost {
cost = inSizeCost
}
outSizeCost := uint64(float64(outSize) * ct.outSizeFactor * globalFactor * maxCostFactor)
if outSizeCost > cost {
cost = outSizeCost
}
return cost
}
var list RequestCostList
for code, data := range reqAvgTimeCost {
list = append(list, requestCostListItem{
MsgCode: code,
BaseCost: maxCost(data.baseCost, reqMaxInSize[code].baseCost, reqMaxOutSize[code].baseCost),
ReqCost: maxCost(data.reqCost, reqMaxInSize[code].reqCost, reqMaxOutSize[code].reqCost),
})
}
return list
}
type gfUpdate struct {
avgTime, servingTime float64
}
// gfLoop starts an event loop which updates the global cost factor which is
// calculated as a weighted average of the average estimate / serving time ratio.
// The applied weight equals the serving time if gfUsage is over a threshold,
// zero otherwise. gfUsage is the recent average serving time per time unit in
// an exponential moving window. This ensures that statistics are collected only
// under high-load circumstances where the measured serving times are relevant.
// The total recharge parameter of the flow control system which controls the
// total allowed serving time per second but nominated in cost units, should
// also be scaled with the cost factor and is also updated by this loop.
func (ct *costTracker) gfLoop() {
var gfUsage, gfSum, gfWeight float64
lastUpdate := mclock.Now()
expUpdate := lastUpdate
data, _ := ct.db.Get([]byte(gfDbKey))
if len(data) == 16 {
gfSum = math.Float64frombits(binary.BigEndian.Uint64(data[0:8]))
gfWeight = math.Float64frombits(binary.BigEndian.Uint64(data[8:16]))
}
if gfWeight < float64(gfInitWeight) {
gfSum = float64(gfInitWeight)
gfWeight = float64(gfInitWeight)
}
gf := gfSum / gfWeight
ct.gf = gf
ct.gfUpdateCh = make(chan gfUpdate, 100)
go func() {
for {
select {
case r := <-ct.gfUpdateCh:
now := mclock.Now()
max := r.servingTime * gf
if r.avgTime > max {
max = r.avgTime
}
dt := float64(now - expUpdate)
expUpdate = now
gfUsage = gfUsage*math.Exp(-dt/float64(gfUsageTC)) + max*1000000/float64(gfUsageTC)
if gfUsage >= gfUsageThreshold*ct.utilTarget*gf {
gfSum += r.avgTime
gfWeight += r.servingTime
if time.Duration(now-lastUpdate) > time.Second {
gf = gfSum / gfWeight
if gfWeight >= float64(gfMaxWeight) {
gfSum = gf * float64(gfMaxWeight)
gfWeight = float64(gfMaxWeight)
}
lastUpdate = now
ct.gfLock.Lock()
ct.gf = gf
ch := ct.totalRechargeCh
ct.gfLock.Unlock()
if ch != nil {
select {
case ct.totalRechargeCh <- uint64(ct.utilTarget * gf):
default:
}
}
log.Debug("global cost factor updated", "gf", gf, "weight", time.Duration(gfWeight))
}
}
case stopCh := <-ct.stopCh:
var data [16]byte
binary.BigEndian.PutUint64(data[0:8], math.Float64bits(gfSum))
binary.BigEndian.PutUint64(data[8:16], math.Float64bits(gfWeight))
ct.db.Put([]byte(gfDbKey), data[:])
log.Debug("global cost factor saved", "sum", time.Duration(gfSum), "weight", time.Duration(gfWeight))
close(stopCh)
return
}
}
}()
}
// globalFactor returns the current value of the global cost factor
func (ct *costTracker) globalFactor() float64 {
ct.gfLock.RLock()
defer ct.gfLock.RUnlock()
return ct.gf
}
// totalRecharge returns the current total recharge parameter which is used by
// flowcontrol.ClientManager and is scaled by the global cost factor
func (ct *costTracker) totalRecharge() uint64 {
ct.gfLock.RLock()
defer ct.gfLock.RUnlock()
return uint64(ct.gf * ct.utilTarget)
}
// subscribeTotalRecharge returns all future updates to the total recharge value
// through a channel and also returns the current value
func (ct *costTracker) subscribeTotalRecharge(ch chan uint64) uint64 {
ct.gfLock.Lock()
defer ct.gfLock.Unlock()
ct.totalRechargeCh = ch
return uint64(ct.gf * ct.utilTarget)
}
// updateStats updates the global cost factor and (if enabled) the real cost vs.
// average estimate statistics
func (ct *costTracker) updateStats(code, amount, servingTime, realCost uint64) {
avg := reqAvgTimeCost[code]
avgTime := avg.baseCost + amount*avg.reqCost
select {
case ct.gfUpdateCh <- gfUpdate{float64(avgTime), float64(servingTime)}:
default:
}
if makeCostStats {
realCost <<= 4
l := 0
for l < 9 && realCost > avgTime {
l++
realCost >>= 1
}
atomic.AddUint64(&ct.stats[code][l], 1)
}
}
// realCost calculates the final cost of a request based on actual serving time,
// incoming and outgoing message size
//
// Note: message size is only taken into account if bandwidth limitation is applied
// and the cost based on either message size is greater than the cost based on
// serving time. A maximum of the three costs is applied instead of their sum
// because the three limited resources (serving thread time and i/o bandwidth) can
// also be maxed out simultaneously.
func (ct *costTracker) realCost(servingTime uint64, inSize, outSize uint32) uint64 {
cost := float64(servingTime)
inSizeCost := float64(inSize) * ct.inSizeFactor
if inSizeCost > cost {
cost = inSizeCost
}
outSizeCost := float64(outSize) * ct.outSizeFactor
if outSizeCost > cost {
cost = outSizeCost
}
return uint64(cost * ct.globalFactor())
}
// printStats prints the distribution of real request cost relative to the average estimates
func (ct *costTracker) printStats() {
if ct.stats == nil {
return
}
for code, arr := range ct.stats {
log.Info("Request cost statistics", "code", code, "1/16", arr[0], "1/8", arr[1], "1/4", arr[2], "1/2", arr[3], "1", arr[4], "2", arr[5], "4", arr[6], "8", arr[7], "16", arr[8], ">16", arr[9])
}
}
type (
// requestCostTable assigns a cost estimate function to each request type
// which is a linear function of the requested amount
// (cost = baseCost + reqCost * amount)
requestCostTable map[uint64]*requestCosts
requestCosts struct {
baseCost, reqCost uint64
}
// RequestCostList is a list representation of request costs which is used for
// database storage and communication through the network
RequestCostList []requestCostListItem
requestCostListItem struct {
MsgCode, BaseCost, ReqCost uint64
}
)
// getCost calculates the estimated cost for a given request type and amount
func (table requestCostTable) getCost(code, amount uint64) uint64 {
costs := table[code]
return costs.baseCost + amount*costs.reqCost
}
// decode converts a cost list to a cost table
2019-05-13 11:26:47 +00:00
func (list RequestCostList) decode(protocolLength uint64) requestCostTable {
les, les/flowcontrol: improved request serving and flow control (#18230) This change - implements concurrent LES request serving even for a single peer. - replaces the request cost estimation method with a cost table based on benchmarks which gives much more consistent results. Until now the allowed number of light peers was just a guess which probably contributed a lot to the fluctuating quality of available service. Everything related to request cost is implemented in a single object, the 'cost tracker'. It uses a fixed cost table with a global 'correction factor'. Benchmark code is included and can be run at any time to adapt costs to low-level implementation changes. - reimplements flowcontrol.ClientManager in a cleaner and more efficient way, with added capabilities: There is now control over bandwidth, which allows using the flow control parameters for client prioritization. Target utilization over 100 percent is now supported to model concurrent request processing. Total serving bandwidth is reduced during block processing to prevent database contention. - implements an RPC API for the LES servers allowing server operators to assign priority bandwidth to certain clients and change prioritized status even while the client is connected. The new API is meant for cases where server operators charge for LES using an off-protocol mechanism. - adds a unit test for the new client manager. - adds an end-to-end test using the network simulator that tests bandwidth control functions through the new API.
2019-02-26 11:32:48 +00:00
table := make(requestCostTable)
for _, e := range list {
2019-05-13 11:26:47 +00:00
if e.MsgCode < protocolLength {
table[e.MsgCode] = &requestCosts{
baseCost: e.BaseCost,
reqCost: e.ReqCost,
}
les, les/flowcontrol: improved request serving and flow control (#18230) This change - implements concurrent LES request serving even for a single peer. - replaces the request cost estimation method with a cost table based on benchmarks which gives much more consistent results. Until now the allowed number of light peers was just a guess which probably contributed a lot to the fluctuating quality of available service. Everything related to request cost is implemented in a single object, the 'cost tracker'. It uses a fixed cost table with a global 'correction factor'. Benchmark code is included and can be run at any time to adapt costs to low-level implementation changes. - reimplements flowcontrol.ClientManager in a cleaner and more efficient way, with added capabilities: There is now control over bandwidth, which allows using the flow control parameters for client prioritization. Target utilization over 100 percent is now supported to model concurrent request processing. Total serving bandwidth is reduced during block processing to prevent database contention. - implements an RPC API for the LES servers allowing server operators to assign priority bandwidth to certain clients and change prioritized status even while the client is connected. The new API is meant for cases where server operators charge for LES using an off-protocol mechanism. - adds a unit test for the new client manager. - adds an end-to-end test using the network simulator that tests bandwidth control functions through the new API.
2019-02-26 11:32:48 +00:00
}
}
return table
}
// testCostList returns a dummy request cost list used by tests
func testCostList() RequestCostList {
cl := make(RequestCostList, len(reqAvgTimeCost))
var max uint64
for code := range reqAvgTimeCost {
if code > max {
max = code
}
}
i := 0
for code := uint64(0); code <= max; code++ {
if _, ok := reqAvgTimeCost[code]; ok {
cl[i].MsgCode = code
cl[i].BaseCost = 0
cl[i].ReqCost = 0
i++
}
}
return cl
}