bsc/p2p/msgrate/msgrate.go
Martin Holst Swende 06151eb581
p2p/msgrate: be more lenient when calculating 'mean' (#25653)
The p2p msgrate tracker is a thing which tries to estimate some mean round-trip times. However, it did so in a very curious way: if a node had 200 peers, it would sort their 200 respective rtt estimates, and then it would pick item number 2 as the mean. So effectively taking third fastest and calling it mean. This probably works "ok" when the number of peers are low (there are other factors too, such as ttlScaling which takes some of the edge off this) -- however when the number of peers is high, it becomes very skewed.

This PR instead bases the 'mean' on the square root of the length of the list. Still pretty harsh, but a bit more lenient.
2022-09-09 10:47:30 +02:00

463 lines
18 KiB
Go

// 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
// 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)
var median time.Duration
switch len(rtts) {
case 0:
median = rttMaxEstimate
case 1:
median = time.Duration(rtts[0])
default:
idx := int(math.Sqrt(float64(len(rtts))))
median = time.Duration(rtts[idx])
}
// 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)
}
}