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Issue 2130493002: Implement THROTTLED priority semantics. (Closed) Base URL: https://chromium.googlesource.com/chromium/src.git@NetworkStreamThrottler
Patch Set: Fix use of message_loop_ in Android tests. Created 4 years, 1 month ago
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1 // Copyright 2016 The Chromium Authors. All rights reserved.
2 // Use of this source code is governed by a BSD-style license that can be
3 // found in the LICENSE file.
4
5 #include "net/base/percentile_estimator.h"
6
7 #include "base/bind.h"
8 #include "testing/gtest/include/gtest/gtest.h"
9
10 namespace {
11
12 // A number to turn sawtooth ramps from 0->100 into something that looks more
13 // random to the algorithm.
14 const int kPrimeMultipleToRandomizeRamps = 71;
15
16 // Random numbers (fixed here for repeatability of tests). Generated originally
17 // by using python's random module with randrange(0,100).
18 int random_numbers[] = {
19 83, 11, 33, 98, 49, 54, 83, 19, 93, 37, 98, 39, 59, 13, 51, 39, 69, 18, 17,
20 17, 6, 85, 95, 51, 83, 39, 18, 82, 88, 47, 69, 27, 20, 82, 86, 38, 98, 65,
21 53, 13, 71, 66, 29, 40, 70, 28, 64, 35, 47, 50, 84, 90, 36, 54, 15, 93, 98,
22 51, 82, 50, 17, 46, 12, 18, 26, 39, 95, 61, 52, 63, 97, 92, 12, 71, 7, 15,
23 74, 10, 64, 57, 25, 82, 95, 40, 76, 8, 28, 83, 58, 1, 22, 58, 17, 33, 61,
24 94, 40, 50, 84, 47, 81, 9, 79, 16, 45, 78, 15, 3, 97, 60, 70, 25, 11, 11,
25 68, 64, 61, 84, 52, 64, 54, 72, 24, 46, 48, 4, 46, 34, 10, 97, 2, 42, 13,
26 9, 95, 75, 11, 99, 92, 33, 65, 48, 19, 72, 63, 39, 0, 10, 83, 62, 12, 99,
27 67, 98, 99, 83, 40, 45, 34, 80, 13, 94, 22, 74, 8, 11, 11, 98, 35, 86, 80,
28 94, 87, 60, 16, 46, 9, 25, 75, 50, 54, 23, 31, 63, 9, 50, 5, 18, 87, 16,
29 47, 72, 24, 93, 14, 1, 26, 41, 50, 49, 41, 77, 54, 48, 50, 3, 50, 16, 54,
30 97, 57, 63, 83, 33, 65, 90, 48, 55, 44, 11, 71, 6, 86, 29, 46, 61, 20, 8,
31 88, 3, 70, 76, 84, 59, 36, 50, 77, 63, 10, 55, 32, 82, 58, 19, 97, 8, 73,
32 47, 55, 74, 46, 52, 62, 19, 65, 75, 57, 23, 98, 39, 63, 19, 75, 48, 93, 58,
33 29, 96, 57, 31, 17, 33, 8, 69, 89, 90, 17, 79, 59, 67, 34, 20, 44, 80, 71,
34 79, 24, 63, 13, 27, 28, 61, 38, 67, 82, 46, 9, 4, 69, 41, 49, 49, 10, 3,
35 93, 46, 57, 96, 78, 51, 45, 37, 0, 6, 99, 93, 87, 18, 72, 83, 95, 39, 54,
36 84, 12, 47, 14, 55, 15, 27, 95, 6, 13, 80, 40, 8, 39, 18, 15, 52, 31, 66,
37 59, 67, 90, 12, 61, 77, 66, 61, 33, 89, 47, 40, 86, 34, 98, 13, 76, 30, 43,
38 56, 57, 88, 34, 48, 67, 6, 29, 92, 38, 11, 23, 74, 45, 38, 35, 94, 15, 72,
39 65, 20, 94, 72, 97, 78, 61, 79, 75, 0, 45, 38, 32, 94, 3, 5, 67, 91, 34,
40 37, 12, 11, 15, 75, 14, 73, 34, 55, 78, 64, 52, 29, 60, 62, 16, 51, 44, 78,
41 0, 15, 41, 5, 52, 4, 68, 53, 39, 39, 68, 71, 66, 68, 97, 65, 55, 39, 94,
42 57, 43, 81, 67, 22, 30, 64, 37, 42, 35, 60, 61, 2, 51, 49, 43, 82, 61, 70,
43 63, 47, 57, 8, 55, 96, 68, 7, 46, 69, 8, 43, 18, 9, 25, 8, 97, 98, 83,
44 79, 19, 92, 54, 90, 72, 80, 92, 94, 26, 48, 94, 74, 32, 29, 44, 34, 55, 56,
45 97, 40, 86, 35, 64, 25, 85, 13, 57, 2, 29, 77, 19, 94, 46, 85, 15, 71, 81,
46 25, 45, 2, 1, 62, 77, 28, 95, 72, 72, 28, 3, 36, 76, 81, 56, 52, 27, 62,
47 8, 5, 62, 1, 43, 68, 40, 68, 22, 65, 30, 50, 36, 89, 5, 71, 68, 99, 53,
48 22, 26, 0, 1, 72, 76, 79, 50, 2, 32, 39, 40, 6, 99, 60, 59, 55, 28, 17,
49 12, 94, 51, 3, 4, 71, 36, 88, 26, 99, 25, 13, 80, 53, 4, 57, 55, 44, 26,
50 82, 4, 53, 34, 47, 16, 97, 56, 30, 0, 73, 85, 59, 86, 24, 70, 73, 53, 68,
51 15, 91, 90, 74, 39, 61, 32, 98, 14, 82, 99, 31, 7, 99, 34, 6, 3, 30, 57,
52 44, 58, 86, 37, 12, 63, 82, 78, 94, 4, 93, 89, 92, 59, 40, 94, 88, 97, 95,
53 5, 88, 40, 80, 79, 0, 2, 46, 86, 46, 75, 87, 86, 8, 23, 35, 62, 79, 66,
54 16, 16, 45, 11, 78, 76, 40, 73, 85, 28, 44, 33, 34, 22, 11, 62, 8, 35, 88,
55 92, 35, 53, 50, 51, 54, 75, 41, 21, 83, 57, 82, 80, 84, 65, 19, 11, 85, 41,
56 80, 86, 62, 34, 54, 54, 79, 81, 52, 87, 54, 54, 43, 17, 44, 63, 54, 14, 88,
57 84, 86, 73, 58, 44, 2, 70, 86, 80, 94, 13, 85, 78, 6, 44, 11, 11, 97, 67,
58 65, 28, 42, 40, 84, 92, 66, 85, 75, 29, 84, 82, 54, 50, 26, 12, 83, 57, 90,
59 9, 40, 69, 38, 70, 65, 76, 85, 76, 4, 30, 86, 43, 79, 77, 69, 53, 35, 12,
60 98, 7, 47, 12, 63, 10, 81, 39, 88, 12, 16, 88, 22, 72, 25, 41, 22, 34, 87,
61 68, 51, 86, 45, 27, 51, 80, 69, 89, 64, 89, 68, 61, 80, 6, 83, 47, 18, 86,
62 73, 16, 61, 89, 47, 5, 33, 59, 47, 75, 15, 60, 28, 18, 59, 65, 51, 13, 28,
63 26, 84, 89, 80, 51, 15, 92, 36, 89, 83, 28, 56, 65, 25, 44, 84, 70, 26, 10,
64 74, 91, 55, 85, 73, 25, 24, 64, 11, 1, 55, 32, 45, 74, 4, 55, 98, 42, 91,
65 88, 18, 79, 37, 15, 5, 98, 63, 65, 77, 66, 18, 99, 1, 78, 96, 15, 16, 16,
66 51, 11, 47, 58, 1, 12, 46, 5, 56, 34, 40, 36, 20, 4, 89, 59, 4, 13, 3,
67 8, 74, 41, 21, 64, 88, 97, 42, 14, 29, 38, 53, 65, 55, 67, 33, 69, 17, 79,
68 45, 2, 63, 2, 97, 47, 73, 22, 86, 32, 31, 95, 90, 84, 25, 86, 91, 77, 1,
69 5, 6, 22, 91, 3, 94, 52, 2, 95, 17, 1, 19, 22, 34, 49, 96, 88, 63, 26,
70 5, 25, 75, 23, 25, 80, 21, 83, 86, 81, 11, 70, 67, 11, 95, 81, 57, 63, 8,
71 43, 60, 40, 42, 67, 50, 2, 51, 43, 34, 7, 1, 90, 59, 74, 87, 23, 23, 71,
72 20, 89, 2, 75, 21, 91, 32, 87, 67, 98, 99, 22, 31, 59, 50, 64, 55, 22, 84,
73 9, 31, 31, 84, 36, 92, 60, 37, 85, 18, 12, 38, 55, 55, 93, 36, 9, 46, 48,
74 24, 91, 60, 95, 55, 73, 63, 27, 55, 96, 79, 50, 41, 5, 67, 85, 99, 95, 3,
75 97, 28, 27, 78, 38, 11, 77, 11, 64, 25, 22, 88, 34, 86, 30, 78, 95, 17, 9,
76 29, 58, 35, 22, 99, 28, 66, 35, 60, 10, 7, 51, 64, 86, 30, 27, 97, 63, 0,
77 36, 87, 52, 16, 5, 90, 8, 66, 58, 91, 85, 3, 95, 31, 73, 87, 30, 78, 46,
78 30, 75, 36, 44, 52, 76, 24, 58, 8, 70, 58, 95, 88, 0, 35, 86, 21, 96, 90,
79 54, 85, 56, 30, 37, 30, 62, 56, 63, 91, 25, 56, 20, 56, 23, 12, 8, 70, 56,
80 83, 49, 70, 67, 61, 95, 50, 41, 88, 37, 89, 37, 21, 63, 25, 46, 16, 75, 73,
81 86, 39, 4, 55, 41, 39, 45, 31, 97, 6, 81, 68, 38, 49, 80, 9, 87, 22, 37,
82 41, 28, 47, 74, 76, 34, 72, 65, 34, 41, 59, 42, 73, 32, 75, 25, 18, 26, 71,
83 93, 92, 12, 76, 93, 84, 44, 43, 4, 9, 3, 90, 91, 45, 0, 10, 43, 45, 65,
84 34, 82, 54, 1, 78, 36, 74, 58, 3, 26, 89, 21, 57, 42, 37, 12, 90, 97, 48,
85 27, 75, 40, 69, 61, 56, 44, 75, 77, 55, 31, 0, 77, 12, 23, 16, 98, 77, 8,
86 96, 92, 91, 26, 50, 42, 65, 38, 58, 41, 45, 69, 42, 37, 89, 92, 40, 74, 68,
87 86, 80, 49, 16, 48, 74, 50, 92, 54, 6, 82, 21, 35, 57, 81, 29, 10, 60, 74,
88 41, 70, 18, 65, 44, 77, 64, 8, 87, 90, 24, 52, 67, 58, 56, 89, 47, 15, 20,
89 4, 87, 72, 87, 13, 79, 3, 26, 43, 52, 72, 83, 17, 99, 29, 10, 61, 62, 42,
90 35, 47, 42, 40, 17, 71, 54, 30, 99, 64, 78, 70, 75, 38, 32, 51, 2, 49, 47,
91 0, 41, 50, 41, 64, 57, 78, 22, 17, 94, 24, 65, 84, 38, 75, 3, 58, 18, 51,
92 91, 72, 91, 55, 6, 70, 76, 73, 30, 54, 73, 77, 45, 85, 88, 58, 25, 80, 35,
93 99, 57, 73, 15, 55, 71, 44, 44, 79, 20, 63, 29, 14, 51, 10, 46, 80, 36, 47,
94 80, 53, 15, 64, 42, 59, 94, 55, 99, 28, 76, 80, 51, 4, 98, 98, 38, 59, 71,
95 9, 93, 91, 46, 74, 63, 10, 39, 1, 43, 11, 64, 39, 59, 54, 9, 44, 78, 52,
96 98, 9, 73, 24, 15, 40, 5, 55, 23, 83, 67, 10, 58, 45, 64, 41, 92, 85, 72,
97 18, 67, 65, 30, 56, 84, 63, 96, 51, 55, 19, 70, 48, 81, 2, 37, 85, 77};
98
99 class PercentileEstimatorTest : public testing::Test {
100 public:
101 PercentileEstimatorTest() : index_(0) {}
102
103 // Create a new estimator with the given parameters.
104 void SetUpEstimator(int percentile, int initial_estimate) {
105 estimator_.reset(
106 new net::PercentileEstimator(percentile, initial_estimate));
107 estimator_->SetRandomNumberGeneratorForTesting(
108 base::Bind(&PercentileEstimatorTest::GetRandomNumber,
109 // Safe since |estimator_| is owned by and
110 // will not survive destruction of |this|.
111 base::Unretained(this)));
112 }
113
114 int CurrentEstimate() { return estimator_->current_estimate(); }
115 void AddSample(int sample) { estimator_->AddSample(sample); }
116
117 // Add the sample until there's a change in the estimate, then return the
118 // new estimate. To get around the randomness of whether samples are
119 // incorporated or not.
120 int AddSampleUntilRegistered(int sample) {
121 int old_estimate = estimator_->current_estimate();
122 while (old_estimate == estimator_->current_estimate())
123 estimator_->AddSample(sample);
124
125 return estimator_->current_estimate();
126 }
127
128 int GetRandomNumber() {
129 int result = random_numbers[index_];
130 ++index_;
131 if (static_cast<unsigned long>(index_) >=
132 sizeof(random_numbers) / sizeof(int)) {
133 index_ = 0;
134 }
135 return result;
136 }
137
138 private:
139 int index_;
140 std::unique_ptr<net::PercentileEstimator> estimator_;
141
142 DISALLOW_COPY_AND_ASSIGN(PercentileEstimatorTest);
143 };
144
145 // Converges upwards fairly quickly.
146 TEST_F(PercentileEstimatorTest, MedianConvergesUpwards) {
147 SetUpEstimator(50, 100);
148
149 for (int i = 0; i < 40; ++i)
150 AddSample(150);
151
152 EXPECT_EQ(150, CurrentEstimate());
153 }
154
155 // Converges downwards fairly quickly.
156 TEST_F(PercentileEstimatorTest, MedianConvergesDownwards) {
157 SetUpEstimator(50, 100);
158
159 for (int i = 0; i < 40; ++i)
160 AddSample(50);
161
162 EXPECT_EQ(50, CurrentEstimate());
163 }
164
165 // Stable if the value is bouncing around.
166 TEST_F(PercentileEstimatorTest, BounceStable) {
167 SetUpEstimator(50, 100);
168
169 for (int i = 0; i < 20; ++i)
170 AddSample(50 + (i % 2) * 100);
171
172 EXPECT_LE(97, CurrentEstimate());
173 EXPECT_LE(CurrentEstimate(), 103);
174 }
175
176 // Correctly converges to a 90%l value upwards.
177 TEST_F(PercentileEstimatorTest, NinetythConvergesUpwards) {
178 SetUpEstimator(90, 50);
179
180 for (int i = 0; i < 10000; ++i)
181 AddSample((i * kPrimeMultipleToRandomizeRamps) % 100);
182
183 EXPECT_LE(86, CurrentEstimate());
184 EXPECT_LE(CurrentEstimate(), 94);
185 }
186
187 // Correctly converges to a 90%l value downwards.
188 TEST_F(PercentileEstimatorTest, NinetythConvergesDownwards) {
189 SetUpEstimator(90, 150);
190
191 for (int i = 0; i < 1000; ++i)
192 AddSample((i * kPrimeMultipleToRandomizeRamps) % 100);
193
194 EXPECT_LT(86, CurrentEstimate());
195 EXPECT_LT(CurrentEstimate(), 94);
196 }
197
198 // Doesn't overshoot sample heading upwards.
199 TEST_F(PercentileEstimatorTest, NoUpwardsOvershoot) {
200 SetUpEstimator(50, 100);
201
202 // Crank up the step size
203 for (int i = 0; i < 20; ++i)
204 AddSample(1000);
205
206 // Derive the step size.
207 int e1 = CurrentEstimate();
208 int e2 = AddSampleUntilRegistered(1000);
209 int step_size = e2 - e1;
210 ASSERT_GT(step_size, 1);
211
212 // Increment by less than the current step size.
213 int new_sample = e2 + step_size / 2;
214 AddSampleUntilRegistered(new_sample);
215 EXPECT_EQ(new_sample, CurrentEstimate());
216 AddSampleUntilRegistered(1000);
217 EXPECT_GT(new_sample + step_size, CurrentEstimate());
218 }
219
220 // Doesn't overshoot sample heading downwards
221 TEST_F(PercentileEstimatorTest, NoDownwardsOvershoot) {
222 SetUpEstimator(50, 1000);
223
224 // Crank up the step size
225 for (int i = 0; i < 20; ++i)
226 AddSample(100);
227
228 // Derive the step size.
229 int e1 = CurrentEstimate();
230 int e2 = AddSampleUntilRegistered(100);
231 int step_size = e1 - e2;
232 ASSERT_GT(step_size, 1);
233
234 // Increment by less than the current step size.
235 int new_sample = e2 - step_size / 2;
236 AddSampleUntilRegistered(new_sample);
237 EXPECT_EQ(new_sample, CurrentEstimate());
238 AddSampleUntilRegistered(100);
239 EXPECT_LT(new_sample - step_size, CurrentEstimate());
240 }
241
242 } // namespace
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