go-ethereum/p2p/msgrate/msgrate.go

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// Copyright 2021 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 msgrate allows estimating the throughput of peers for more balanced syncs.
package msgrate
import (
"errors"
"math"
"sort"
"sync"
"time"
"github.com/ethereum/go-ethereum/log"
)
// measurementImpact is the impact a single measurement has on a peer's final
// capacity value. A value closer to 0 reacts slower to sudden network changes,
// but it is also more stable against temporary hiccups. 0.1 worked well for
// most of Ethereum's existence, so might as well go with it.
const measurementImpact = 0.1
// capacityOverestimation is the ratio of items to over-estimate when retrieving
// a peer's capacity to avoid locking into a lower value due to never attempting
// to fetch more than some local stable value.
const capacityOverestimation = 1.01
// qosTuningPeers is the number of best peers to tune round trip times based on.
// An Ethereum node doesn't need hundreds of connections to operate correctly,
// so instead of lowering our download speed to the median of potentially many
// bad nodes, we can target a smaller set of vey good nodes. At worse this will
// result in less nodes to sync from, but that's still better than some hogging
// the pipeline.
const qosTuningPeers = 5
// rttMinEstimate is the minimal round trip time to target requests for. Since
// every request entails a 2 way latency + bandwidth + serving database lookups,
// it should be generous enough to permit meaningful work to be done on top of
// the transmission costs.
const rttMinEstimate = 2 * time.Second
// rttMaxEstimate is the maximal round trip time to target requests for. Although
// the expectation is that a well connected node will never reach this, certain
// special connectivity ones might experience significant delays (e.g. satellite
// uplink with 3s RTT). This value should be low enough to forbid stalling the
// pipeline too long, but large enough to cover the worst of the worst links.
const rttMaxEstimate = 20 * time.Second
// rttPushdownFactor is a multiplier to attempt forcing quicker requests than
// what the message rate tracker estimates. The reason is that message rate
// tracking adapts queries to the RTT, but multiple RTT values can be perfectly
// valid, they just result in higher packet sizes. Since smaller packets almost
// always result in stabler download streams, this factor hones in on the lowest
// RTT from all the functional ones.
const rttPushdownFactor = 0.9
// rttMinConfidence is the minimum value the roundtrip confidence factor may drop
// to. Since the target timeouts are based on how confident the tracker is in the
// true roundtrip, it's important to not allow too huge fluctuations.
const rttMinConfidence = 0.1
// ttlScaling is the multiplier that converts the estimated roundtrip time to a
// timeout cap for network requests. The expectation is that peers' response time
// will fluctuate around the estimated roundtrip, but depending in their load at
// request time, it might be higher than anticipated. This scaling factor ensures
// that we allow remote connections some slack but at the same time do enforce a
// behavior similar to our median peers.
const ttlScaling = 3
// ttlLimit is the maximum timeout allowance to prevent reaching crazy numbers
// if some unforeseen network events shappen. As much as we try to hone in on
// the most optimal values, it doesn't make any sense to go above a threshold,
// even if everything is slow and screwy.
const ttlLimit = time.Minute
// tuningConfidenceCap is the number of active peers above which to stop detuning
// the confidence number. The idea here is that once we hone in on the capacity
// of a meaningful number of peers, adding one more should ot have a significant
// impact on things, so just ron with the originals.
const tuningConfidenceCap = 10
// tuningImpact is the influence that a new tuning target has on the previously
// cached value. This number is mostly just an out-of-the-blue heuristic that
// prevents the estimates from jumping around. There's no particular reason for
// the current value.
const tuningImpact = 0.25
// Tracker estimates the throughput capacity of a peer with regard to each data
// type it can deliver. The goal is to dynamically adjust request sizes to max
// out network throughput without overloading either the peer or th elocal node.
//
// By tracking in real time the latencies and bandiwdths peers exhibit for each
// packet type, it's possible to prevent overloading by detecting a slowdown on
// one type when another type is pushed too hard.
//
// Similarly, real time measurements also help avoid overloading the local net
// connection if our peers would otherwise be capable to deliver more, but the
// local link is saturated. In that case, the live measurements will force us
// to reduce request sizes until the throughput gets stable.
//
// Lastly, message rate measurements allows us to detect if a peer is unusually
// slow compared to other peers, in which case we can decide to keep it around
// or free up the slot so someone closer.
//
// Since throughput tracking and estimation adapts dynamically to live network
// conditions, it's fine to have multiple trackers locally track the same peer
// in different subsystem. The throughput will simply be distributed across the
// two trackers if both are highly active.
type Tracker struct {
// capacity is the number of items retrievable per second of a given type.
// It is analogous to bandwidth, but we deliberately avoided using bytes
// as the unit, since serving nodes also spend a lot of time loading data
// from disk, which is linear in the number of items, but mostly constant
// in their sizes.
//
// Callers of course are free to use the item counter as a byte counter if
// or when their protocol of choice if capped by bytes instead of items.
// (eg. eth.getHeaders vs snap.getAccountRange).
capacity map[uint64]float64
// roundtrip is the latency a peer in general responds to data requests.
// This number is not used inside the tracker, but is exposed to compare
// peers to each other and filter out slow ones. Note however, it only
// makes sense to compare RTTs if the caller caters request sizes for
// each peer to target the same RTT. There's no need to make this number
// the real networking RTT, we just need a number to compare peers with.
roundtrip time.Duration
lock sync.RWMutex
}
// NewTracker creates a new message rate tracker for a specific peer. An initial
// RTT is needed to avoid a peer getting marked as an outlier compared to others
// right after joining. It's suggested to use the median rtt across all peers to
// init a new peer tracker.
func NewTracker(caps map[uint64]float64, rtt time.Duration) *Tracker {
if caps == nil {
caps = make(map[uint64]float64)
}
return &Tracker{
capacity: caps,
roundtrip: rtt,
}
}
// Capacity calculates the number of items the peer is estimated to be able to
// retrieve within the allotted time slot. The method will round up any division
// errors and will add an additional overestimation ratio on top. The reason for
// overshooting the capacity is because certain message types might not increase
// the load proportionally to the requested items, so fetching a bit more might
// still take the same RTT. By forcefully overshooting by a small amount, we can
// avoid locking into a lower-that-real capacity.
func (t *Tracker) Capacity(kind uint64, targetRTT time.Duration) int {
t.lock.RLock()
defer t.lock.RUnlock()
// Calculate the actual measured throughput
throughput := t.capacity[kind] * float64(targetRTT) / float64(time.Second)
// Return an overestimation to force the peer out of a stuck minima, adding
// +1 in case the item count is too low for the overestimator to dent
return roundCapacity(1 + capacityOverestimation*throughput)
}
// roundCapacity gives the integer value of a capacity.
// The result fits int32, and is guaranteed to be positive.
func roundCapacity(cap float64) int {
const maxInt32 = float64(1<<31 - 1)
return int(math.Min(maxInt32, math.Max(1, math.Ceil(cap))))
}
// Update modifies the peer's capacity values for a specific data type with a new
// measurement. If the delivery is zero, the peer is assumed to have either timed
// out or to not have the requested data, resulting in a slash to 0 capacity. This
// avoids assigning the peer retrievals that it won't be able to honour.
func (t *Tracker) Update(kind uint64, elapsed time.Duration, items int) {
t.lock.Lock()
defer t.lock.Unlock()
// If nothing was delivered (timeout / unavailable data), reduce throughput
// to minimum
if items == 0 {
t.capacity[kind] = 0
return
}
// Otherwise update the throughput with a new measurement
if elapsed <= 0 {
elapsed = 1 // +1 (ns) to ensure non-zero divisor
}
measured := float64(items) / (float64(elapsed) / float64(time.Second))
t.capacity[kind] = (1-measurementImpact)*(t.capacity[kind]) + measurementImpact*measured
t.roundtrip = time.Duration((1-measurementImpact)*float64(t.roundtrip) + measurementImpact*float64(elapsed))
}
// Trackers is a set of message rate trackers across a number of peers with the
// goal of aggregating certain measurements across the entire set for outlier
// filtering and newly joining initialization.
type Trackers struct {
trackers map[string]*Tracker
// roundtrip is the current best guess as to what is a stable round trip time
// across the entire collection of connected peers. This is derived from the
// various trackers added, but is used as a cache to avoid recomputing on each
// network request. The value is updated once every RTT to avoid fluctuations
// caused by hiccups or peer events.
roundtrip time.Duration
// confidence represents the probability that the estimated roundtrip value
// is the real one across all our peers. The confidence value is used as an
// impact factor of new measurements on old estimates. As our connectivity
// stabilizes, this value gravitates towards 1, new measurements havinng
// almost no impact. If there's a large peer churn and few peers, then new
// measurements will impact it more. The confidence is increased with every
// packet and dropped with every new connection.
confidence float64
// tuned is the time instance the tracker recalculated its cached roundtrip
// value and confidence values. A cleaner way would be to have a heartbeat
// goroutine do it regularly, but that requires a lot of maintenance to just
// run every now and again.
tuned time.Time
// The fields below can be used to override certain default values. Their
// purpose is to allow quicker tests. Don't use them in production.
OverrideTTLLimit time.Duration
log log.Logger
lock sync.RWMutex
}
// NewTrackers creates an empty set of trackers to be filled with peers.
func NewTrackers(log log.Logger) *Trackers {
return &Trackers{
trackers: make(map[string]*Tracker),
roundtrip: rttMaxEstimate,
confidence: 1,
tuned: time.Now(),
OverrideTTLLimit: ttlLimit,
log: log,
}
}
// Track inserts a new tracker into the set.
func (t *Trackers) Track(id string, tracker *Tracker) error {
t.lock.Lock()
defer t.lock.Unlock()
if _, ok := t.trackers[id]; ok {
return errors.New("already tracking")
}
t.trackers[id] = tracker
t.detune()
return nil
}
// Untrack stops tracking a previously added peer.
func (t *Trackers) Untrack(id string) error {
t.lock.Lock()
defer t.lock.Unlock()
if _, ok := t.trackers[id]; !ok {
return errors.New("not tracking")
}
delete(t.trackers, id)
return nil
}
// MedianRoundTrip returns the median RTT across all known trackers. The purpose
// of the median RTT is to initialize a new peer with sane statistics that it will
// hopefully outperform. If it seriously underperforms, there's a risk of dropping
// the peer, but that is ok as we're aiming for a strong median.
func (t *Trackers) MedianRoundTrip() time.Duration {
t.lock.RLock()
defer t.lock.RUnlock()
return t.medianRoundTrip()
}
// medianRoundTrip is the internal lockless version of MedianRoundTrip to be used
// by the QoS tuner.
func (t *Trackers) medianRoundTrip() time.Duration {
// Gather all the currently measured round trip times
rtts := make([]float64, 0, len(t.trackers))
for _, tt := range t.trackers {
tt.lock.RLock()
rtts = append(rtts, float64(tt.roundtrip))
tt.lock.RUnlock()
}
sort.Float64s(rtts)
median := rttMaxEstimate
if qosTuningPeers <= len(rtts) {
median = time.Duration(rtts[qosTuningPeers/2]) // Median of our best few peers
} else if len(rtts) > 0 {
median = time.Duration(rtts[len(rtts)/2]) // Median of all out connected peers
}
// Restrict the RTT into some QoS defaults, irrelevant of true RTT
if median < rttMinEstimate {
median = rttMinEstimate
}
if median > rttMaxEstimate {
median = rttMaxEstimate
}
return median
}
// MeanCapacities returns the capacities averaged across all the added trackers.
// The purpos of the mean capacities are to initialize a new peer with some sane
// starting values that it will hopefully outperform. If the mean overshoots, the
// peer will be cut back to minimal capacity and given another chance.
func (t *Trackers) MeanCapacities() map[uint64]float64 {
t.lock.RLock()
defer t.lock.RUnlock()
return t.meanCapacities()
}
// meanCapacities is the internal lockless version of MeanCapacities used for
// debug logging.
func (t *Trackers) meanCapacities() map[uint64]float64 {
capacities := make(map[uint64]float64)
for _, tt := range t.trackers {
tt.lock.RLock()
for key, val := range tt.capacity {
capacities[key] += val
}
tt.lock.RUnlock()
}
for key, val := range capacities {
capacities[key] = val / float64(len(t.trackers))
}
return capacities
}
// TargetRoundTrip returns the current target round trip time for a request to
// complete in.The returned RTT is slightly under the estimated RTT. The reason
// is that message rate estimation is a 2 dimensional problem which is solvable
// for any RTT. The goal is to gravitate towards smaller RTTs instead of large
// messages, to result in a stabler download stream.
func (t *Trackers) TargetRoundTrip() time.Duration {
// Recalculate the internal caches if it's been a while
t.tune()
// Caches surely recent, return target roundtrip
t.lock.RLock()
defer t.lock.RUnlock()
return time.Duration(float64(t.roundtrip) * rttPushdownFactor)
}
// TargetTimeout returns the timeout allowance for a single request to finish
// under. The timeout is proportional to the roundtrip, but also takes into
// consideration the tracker's confidence in said roundtrip and scales it
// accordingly. The final value is capped to avoid runaway requests.
func (t *Trackers) TargetTimeout() time.Duration {
// Recalculate the internal caches if it's been a while
t.tune()
// Caches surely recent, return target timeout
t.lock.RLock()
defer t.lock.RUnlock()
return t.targetTimeout()
}
// targetTimeout is the internal lockless version of TargetTimeout to be used
// during QoS tuning.
func (t *Trackers) targetTimeout() time.Duration {
timeout := time.Duration(ttlScaling * float64(t.roundtrip) / t.confidence)
if timeout > t.OverrideTTLLimit {
timeout = t.OverrideTTLLimit
}
return timeout
}
// tune gathers the individual tracker statistics and updates the estimated
// request round trip time.
func (t *Trackers) tune() {
// Tune may be called concurrently all over the place, but we only want to
// periodically update and even then only once. First check if it was updated
// recently and abort if so.
t.lock.RLock()
dirty := time.Since(t.tuned) > t.roundtrip
t.lock.RUnlock()
if !dirty {
return
}
// If an update is needed, obtain a write lock but make sure we don't update
// it on all concurrent threads one by one.
t.lock.Lock()
defer t.lock.Unlock()
if dirty := time.Since(t.tuned) > t.roundtrip; !dirty {
return // A concurrent request beat us to the tuning
}
// First thread reaching the tuning point, update the estimates and return
t.roundtrip = time.Duration((1-tuningImpact)*float64(t.roundtrip) + tuningImpact*float64(t.medianRoundTrip()))
t.confidence = t.confidence + (1-t.confidence)/2
t.tuned = time.Now()
t.log.Debug("Recalculated msgrate QoS values", "rtt", t.roundtrip, "confidence", t.confidence, "ttl", t.targetTimeout(), "next", t.tuned.Add(t.roundtrip))
t.log.Trace("Debug dump of mean capacities", "caps", log.Lazy{Fn: t.meanCapacities})
}
// detune reduces the tracker's confidence in order to make fresh measurements
// have a larger impact on the estimates. It is meant to be used during new peer
// connections so they can have a proper impact on the estimates.
func (t *Trackers) detune() {
// If we have a single peer, confidence is always 1
if len(t.trackers) == 1 {
t.confidence = 1
return
}
// If we have a ton of peers, don't drop the confidence since there's enough
// remaining to retain the same throughput
if len(t.trackers) >= tuningConfidenceCap {
return
}
// Otherwise drop the confidence factor
peers := float64(len(t.trackers))
t.confidence = t.confidence * (peers - 1) / peers
if t.confidence < rttMinConfidence {
t.confidence = rttMinConfidence
}
t.log.Debug("Relaxed msgrate QoS values", "rtt", t.roundtrip, "confidence", t.confidence, "ttl", t.targetTimeout())
}
// Capacity is a helper function to access a specific tracker without having to
// track it explicitly outside.
func (t *Trackers) Capacity(id string, kind uint64, targetRTT time.Duration) int {
t.lock.RLock()
defer t.lock.RUnlock()
tracker := t.trackers[id]
if tracker == nil {
return 1 // Unregister race, don't return 0, it's a dangerous number
}
return tracker.Capacity(kind, targetRTT)
}
// Update is a helper function to access a specific tracker without having to
// track it explicitly outside.
func (t *Trackers) Update(id string, kind uint64, elapsed time.Duration, items int) {
t.lock.RLock()
defer t.lock.RUnlock()
if tracker := t.trackers[id]; tracker != nil {
tracker.Update(kind, elapsed, items)
}
}