plugeth/les/flowcontrol/manager_test.go

126 lines
3.9 KiB
Go
Raw Normal View History

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 2018 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 flowcontrol
import (
"math/rand"
"testing"
"time"
"github.com/ethereum/go-ethereum/common/mclock"
)
type testNode struct {
node *ClientNode
bufLimit, capacity uint64
waitUntil mclock.AbsTime
index, totalCost uint64
}
const (
testMaxCost = 1000000
testLength = 100000
)
// testConstantTotalCapacity simulates multiple request sender nodes and verifies
// whether the total amount of served requests matches the expected value based on
// the total capacity and the duration of the test.
// Some nodes are sending requests occasionally so that their buffer should regularly
// reach the maximum while other nodes (the "max capacity nodes") are sending at the
// maximum permitted rate. The max capacity nodes are changed multiple times during
// a single test.
func TestConstantTotalCapacity(t *testing.T) {
testConstantTotalCapacity(t, 10, 1, 0)
testConstantTotalCapacity(t, 10, 1, 1)
testConstantTotalCapacity(t, 30, 1, 0)
testConstantTotalCapacity(t, 30, 2, 3)
testConstantTotalCapacity(t, 100, 1, 0)
testConstantTotalCapacity(t, 100, 3, 5)
testConstantTotalCapacity(t, 100, 5, 10)
}
func testConstantTotalCapacity(t *testing.T, nodeCount, maxCapacityNodes, randomSend int) {
clock := &mclock.Simulated{}
nodes := make([]*testNode, nodeCount)
var totalCapacity uint64
for i := range nodes {
nodes[i] = &testNode{capacity: uint64(50000 + rand.Intn(100000))}
totalCapacity += nodes[i].capacity
}
m := NewClientManager(PieceWiseLinear{{0, totalCapacity}}, clock)
for _, n := range nodes {
n.bufLimit = n.capacity * 6000
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
n.node = NewClientNode(m, ServerParams{BufLimit: n.bufLimit, MinRecharge: n.capacity})
}
maxNodes := make([]int, maxCapacityNodes)
for i := range maxNodes {
// we don't care if some indexes are selected multiple times
// in that case we have fewer max nodes
maxNodes[i] = rand.Intn(nodeCount)
}
var sendCount int
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
for i := 0; i < testLength; i++ {
now := clock.Now()
for _, idx := range maxNodes {
for nodes[idx].send(t, now) {
}
}
if rand.Intn(testLength) < maxCapacityNodes*3 {
maxNodes[rand.Intn(maxCapacityNodes)] = rand.Intn(nodeCount)
}
sendCount += randomSend
failCount := randomSend * 10
for sendCount > 0 && failCount > 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.
2019-02-26 11:32:48 +00:00
if nodes[rand.Intn(nodeCount)].send(t, now) {
sendCount--
} else {
failCount--
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
}
}
clock.Run(time.Millisecond)
}
var totalCost uint64
for _, n := range nodes {
totalCost += n.totalCost
}
ratio := float64(totalCost) / float64(totalCapacity) / testLength
if ratio < 0.98 || ratio > 1.02 {
t.Errorf("totalCost/totalCapacity/testLength ratio incorrect (expected: 1, got: %f)", ratio)
}
}
func (n *testNode) send(t *testing.T, now mclock.AbsTime) bool {
if now < n.waitUntil {
return false
}
n.index++
if ok, _, _ := n.node.AcceptRequest(0, n.index, testMaxCost); !ok {
t.Fatalf("Rejected request after expected waiting time has passed")
}
rcost := uint64(rand.Int63n(testMaxCost))
bv := n.node.RequestProcessed(0, n.index, testMaxCost, rcost)
if bv < testMaxCost {
n.waitUntil = now + mclock.AbsTime((testMaxCost-bv)*1001000/n.capacity)
}
n.totalCost += rcost
return true
}