Official Go implementation of the Ethereum protocol
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go-ethereum/les/servingqueue.go

365 lines
10 KiB

// Copyright 2019 The go-ethereum Authors
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.
6 years ago
// 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 les
import (
"sync"
"sync/atomic"
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.
6 years ago
"github.com/ethereum/go-ethereum/common/mclock"
"github.com/ethereum/go-ethereum/common/prque"
"golang.org/x/exp/slices"
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.
6 years ago
)
// servingQueue allows running tasks in a limited number of threads and puts the
// waiting tasks in a priority queue
type servingQueue struct {
recentTime, queuedTime, servingTimeDiff uint64
burstLimit, burstDropLimit uint64
burstDecRate float64
lastUpdate mclock.AbsTime
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.
6 years ago
queueAddCh, queueBestCh chan *servingTask
stopThreadCh, quit chan struct{}
setThreadsCh chan int
wg sync.WaitGroup
threadCount int // number of currently running threads
queue *prque.Prque[int64, *servingTask] // priority queue for waiting or suspended tasks
best *servingTask // the highest priority task (not included in the queue)
suspendBias int64 // priority bias against suspending an already running task
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.
6 years ago
}
// servingTask represents a request serving task. Tasks can be implemented to
// run in multiple steps, allowing the serving queue to suspend execution between
// steps if higher priority tasks are entered. The creator of the task should
// set the following fields:
//
// - priority: greater value means higher priority; values can wrap around the int64 range
// - run: execute a single step; return true if finished
// - after: executed after run finishes or returns an error, receives the total serving time
type servingTask struct {
sq *servingQueue
servingTime, timeAdded, maxTime, expTime uint64
peer *clientPeer
priority int64
biasAdded bool
token runToken
tokenCh chan runToken
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.
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}
// runToken received by servingTask.start allows the task to run. Closing the
// channel by servingTask.stop signals the thread controller to allow a new task
// to start running.
type runToken chan struct{}
// start blocks until the task can start and returns true if it is allowed to run.
// Returning false means that the task should be cancelled.
func (t *servingTask) start() bool {
if t.peer.isFrozen() {
return false
}
t.tokenCh = make(chan runToken, 1)
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.
6 years ago
select {
case t.sq.queueAddCh <- t:
case <-t.sq.quit:
return false
}
select {
case t.token = <-t.tokenCh:
case <-t.sq.quit:
return false
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.
6 years ago
}
if t.token == nil {
return false
}
t.servingTime -= uint64(mclock.Now())
return true
}
// done signals the thread controller about the task being finished and returns
// the total serving time of the task in nanoseconds.
func (t *servingTask) done() uint64 {
t.servingTime += uint64(mclock.Now())
close(t.token)
diff := t.servingTime - t.timeAdded
t.timeAdded = t.servingTime
if t.expTime > diff {
t.expTime -= diff
atomic.AddUint64(&t.sq.servingTimeDiff, t.expTime)
} else {
t.expTime = 0
}
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.
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return t.servingTime
}
// waitOrStop can be called during the execution of the task. It blocks if there
// is a higher priority task waiting (a bias is applied in favor of the currently
// running task). Returning true means that the execution can be resumed. False
// means the task should be cancelled.
func (t *servingTask) waitOrStop() bool {
t.done()
if !t.biasAdded {
t.priority += t.sq.suspendBias
t.biasAdded = true
}
return t.start()
}
// newServingQueue returns a new servingQueue
func newServingQueue(suspendBias int64, utilTarget float64) *servingQueue {
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.
6 years ago
sq := &servingQueue{
queue: prque.New[int64, *servingTask](nil),
suspendBias: suspendBias,
queueAddCh: make(chan *servingTask, 100),
queueBestCh: make(chan *servingTask),
stopThreadCh: make(chan struct{}),
quit: make(chan struct{}),
setThreadsCh: make(chan int, 10),
burstLimit: uint64(utilTarget * bufLimitRatio * 1200000),
burstDropLimit: uint64(utilTarget * bufLimitRatio * 1000000),
burstDecRate: utilTarget,
lastUpdate: mclock.Now(),
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.
6 years ago
}
sq.wg.Add(2)
go sq.queueLoop()
go sq.threadCountLoop()
return sq
}
// newTask creates a new task with the given priority
func (sq *servingQueue) newTask(peer *clientPeer, maxTime uint64, priority int64) *servingTask {
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.
6 years ago
return &servingTask{
sq: sq,
peer: peer,
maxTime: maxTime,
expTime: maxTime,
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.
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priority: priority,
}
}
// threadController is started in multiple goroutines and controls the execution
// of tasks. The number of active thread controllers equals the allowed number of
// concurrently running threads. It tries to fetch the highest priority queued
// task first. If there are no queued tasks waiting then it can directly catch
// run tokens from the token channel and allow the corresponding tasks to run
// without entering the priority queue.
func (sq *servingQueue) threadController() {
defer sq.wg.Done()
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.
6 years ago
for {
token := make(runToken)
select {
case best := <-sq.queueBestCh:
best.tokenCh <- token
case <-sq.stopThreadCh:
return
case <-sq.quit:
return
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.
6 years ago
}
select {
case <-sq.stopThreadCh:
return
case <-sq.quit:
return
case <-token:
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.
6 years ago
}
}
}
// peerTasks lists the tasks received from a given peer when selecting peers to freeze
type peerTasks struct {
peer *clientPeer
list []*servingTask
sumTime uint64
priority float64
}
// freezePeers selects the peers with the worst priority queued tasks and freezes
// them until burstTime goes under burstDropLimit or all peers are frozen
func (sq *servingQueue) freezePeers() {
peerMap := make(map[*clientPeer]*peerTasks)
var peerList []*peerTasks
if sq.best != nil {
sq.queue.Push(sq.best, sq.best.priority)
}
sq.best = nil
for sq.queue.Size() > 0 {
task := sq.queue.PopItem()
tasks := peerMap[task.peer]
if tasks == nil {
bufValue, bufLimit := task.peer.fcClient.BufferStatus()
if bufLimit < 1 {
bufLimit = 1
}
tasks = &peerTasks{
peer: task.peer,
priority: float64(bufValue) / float64(bufLimit), // lower value comes first
}
peerMap[task.peer] = tasks
peerList = append(peerList, tasks)
}
tasks.list = append(tasks.list, task)
tasks.sumTime += task.expTime
}
slices.SortFunc(peerList, func(a, b *peerTasks) int {
if a.priority < b.priority {
return -1
}
if a.priority > b.priority {
return 1
}
return 0
})
drop := true
for _, tasks := range peerList {
if drop {
tasks.peer.freeze()
tasks.peer.fcClient.Freeze()
sq.queuedTime -= tasks.sumTime
sqQueuedGauge.Update(int64(sq.queuedTime))
clientFreezeMeter.Mark(1)
drop = sq.recentTime+sq.queuedTime > sq.burstDropLimit
for _, task := range tasks.list {
task.tokenCh <- nil
}
} else {
for _, task := range tasks.list {
sq.queue.Push(task, task.priority)
}
}
}
if sq.queue.Size() > 0 {
sq.best = sq.queue.PopItem()
}
}
// updateRecentTime recalculates the recent serving time value
func (sq *servingQueue) updateRecentTime() {
subTime := atomic.SwapUint64(&sq.servingTimeDiff, 0)
now := mclock.Now()
dt := now - sq.lastUpdate
sq.lastUpdate = now
if dt > 0 {
subTime += uint64(float64(dt) * sq.burstDecRate)
}
if sq.recentTime > subTime {
sq.recentTime -= subTime
} else {
sq.recentTime = 0
}
}
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.
6 years ago
// addTask inserts a task into the priority queue
func (sq *servingQueue) addTask(task *servingTask) {
if sq.best == nil {
sq.best = task
} else if task.priority-sq.best.priority > 0 {
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.
6 years ago
sq.queue.Push(sq.best, sq.best.priority)
sq.best = task
} else {
sq.queue.Push(task, task.priority)
}
sq.updateRecentTime()
sq.queuedTime += task.expTime
sqServedGauge.Update(int64(sq.recentTime))
sqQueuedGauge.Update(int64(sq.queuedTime))
if sq.recentTime+sq.queuedTime > sq.burstLimit {
sq.freezePeers()
}
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.
6 years ago
}
// queueLoop is an event loop running in a goroutine. It receives tasks from queueAddCh
// and always tries to send the highest priority task to queueBestCh. Successfully sent
// tasks are removed from the queue.
func (sq *servingQueue) queueLoop() {
defer sq.wg.Done()
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.
6 years ago
for {
if sq.best != nil {
expTime := sq.best.expTime
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.
6 years ago
select {
case task := <-sq.queueAddCh:
sq.addTask(task)
case sq.queueBestCh <- sq.best:
sq.updateRecentTime()
sq.queuedTime -= expTime
sq.recentTime += expTime
sqServedGauge.Update(int64(sq.recentTime))
sqQueuedGauge.Update(int64(sq.queuedTime))
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.
6 years ago
if sq.queue.Size() == 0 {
sq.best = nil
} else {
sq.best = sq.queue.PopItem()
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.
6 years ago
}
case <-sq.quit:
return
}
} else {
select {
case task := <-sq.queueAddCh:
sq.addTask(task)
case <-sq.quit:
return
}
}
}
}
// threadCountLoop is an event loop running in a goroutine. It adjusts the number
// of active thread controller goroutines.
func (sq *servingQueue) threadCountLoop() {
var threadCountTarget int
defer sq.wg.Done()
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.
6 years ago
for {
for threadCountTarget > sq.threadCount {
sq.wg.Add(1)
go sq.threadController()
sq.threadCount++
}
if threadCountTarget < sq.threadCount {
select {
case threadCountTarget = <-sq.setThreadsCh:
case sq.stopThreadCh <- struct{}{}:
sq.threadCount--
case <-sq.quit:
return
}
} else {
select {
case threadCountTarget = <-sq.setThreadsCh:
case <-sq.quit:
return
}
}
}
}
// setThreads sets the allowed processing thread count, suspending tasks as soon as
// possible if necessary.
func (sq *servingQueue) setThreads(threadCount int) {
select {
case sq.setThreadsCh <- threadCount:
case <-sq.quit:
return
}
}
// stop stops task processing as soon as possible and shuts down the serving queue.
func (sq *servingQueue) stop() {
close(sq.quit)
sq.wg.Wait()
}