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Merge pull request #2446 from brave/riastradh-4435-exponrate
Implement and use exponentially/geometrically distributed delays.
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,22 @@ | ||
| # This Source Code Form is subject to the terms of the Mozilla Public | ||
| # License, v. 2.0. If a copy of the MPL was not distributed with this file, | ||
| # You can obtain one at http://mozilla.org/MPL/2.0/. | ||
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| config("external_config") { | ||
| include_dirs = [ ".." ] | ||
| } | ||
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| source_set("brave_base") { | ||
| public_configs = [ ":external_config" ] | ||
| configs += [ ":external_config" ] | ||
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| sources = [ | ||
| "random.cc", | ||
| "random.h", | ||
| ] | ||
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| deps = [ | ||
| "//base", | ||
| "//crypto", | ||
| ] | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,125 @@ | ||
| /* Copyright (c) 2019 The Brave Authors. All rights reserved. | ||
| * This Source Code Form is subject to the terms of the Mozilla Public | ||
| * License, v. 2.0. If a copy of the MPL was not distributed with this file, | ||
| * You can obtain one at http://mozilla.org/MPL/2.0/. */ | ||
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| #include "brave_base/random.h" | ||
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| #include <cmath> | ||
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| #include "base/bits.h" | ||
| #include "crypto/random.h" | ||
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| namespace brave_base { | ||
| namespace random { | ||
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| uint64_t Uniform64() { | ||
| uint64_t x; | ||
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| crypto::RandBytes(&x, sizeof x); | ||
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| return x; | ||
| } | ||
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| // Correct floating-point uniform [0,1] sampler which gives exactly | ||
| // the correct weight to every floating-point number in [0,1], | ||
| // i.e. the Lebesgue measure of the set of real numbers that is | ||
| // rounded to it. | ||
| // | ||
| // In principle this algorithm could return any floating-point number | ||
| // in [0,1], but in practice it cannot return 0 because the | ||
| // probability is 2^-1075; consequently you can reliably pass the | ||
| // result to, e.g., log, and be guaranteed to get a finite result. | ||
| // | ||
| // In contrast, if we simply divided a uniform random 53-bit or 64-bit | ||
| // integer by 2^53 or 2^64, the result would _not_ be guaranteed to be | ||
| // nonzero, _and_ it would exclude the result 1, which it should | ||
| // return with probability 2^-54. | ||
| double Uniform_01() { | ||
| uint64_t e, x, u; | ||
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| // Draw an exponent with geometric distribution. | ||
| e = 0; | ||
| do { | ||
| if ((x = Uniform64()) != 0) | ||
| break; | ||
| e += 64; | ||
| } while (e < 1088); | ||
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| // Count the remaining leading zero bits to finish up the geometric | ||
| // draw. | ||
| // | ||
| // If we stopped at e >= 1088, this means our RNG is broken. In | ||
| // that case, we could just as well abort the process. But it is | ||
| // also safe to call CountLeadingZeroBits at this point; it will | ||
| // just return 64, and the exponent will be even more improbably | ||
| // larger. | ||
| e += base::bits::CountLeadingZeroBits(x); | ||
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| u = Uniform64(); | ||
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| return deterministic::Uniform_01(e, u); | ||
| } | ||
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| // Nondeterministic distribution samplers. These should call | ||
| // Uniform64 and Uniform_01 only, and pass them on to a deterministic | ||
| // transform in order to facilitate automatic testing. | ||
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| double Exponential(double rate) { | ||
| uint64_t s = Uniform64(); | ||
| double p0 = Uniform_01(); | ||
| return deterministic::Exponential(s, p0, rate); | ||
| } | ||
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| uint64_t Geometric(double period) { | ||
| uint64_t s = Uniform64(); | ||
| double p0 = Uniform_01(); | ||
| return deterministic::Geometric(s, p0, period); | ||
| } | ||
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| namespace deterministic { | ||
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| double StdExponential(uint64_t s, double p0) { | ||
| // We want to evaluate log(p) for p near 0, and log1p(-p) for p near | ||
| // 1. We will decide which half of the interval we're lying in by a | ||
| // coin toss, and then scale p0 appropriately. | ||
| p0 *= 0.5; | ||
| return ((s & 1) == 0) ? -log(p0) : -log1p(-p0); | ||
| } | ||
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| double Exponential(uint64_t s, double p0, double rate) { | ||
| return StdExponential(s, p0)/rate; | ||
| } | ||
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| uint64_t Geometric(uint64_t s, double p0, double period) { | ||
| return floor(StdExponential(s, p0)*period); | ||
| } | ||
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| // If e has geometric distribution and u has uniform distribution, | ||
| // Uniform_01(e, u) has uniform distribution in [0, 1]. | ||
| double Uniform_01(uint64_t e, uint64_t u) { | ||
| double s; | ||
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| // Pick a normalized odd significand in (2^63, 2^64). Choosing an | ||
| // odd significand breaks ties, which occur with Lebesgue measure | ||
| // zero in the reals but with nonzero probability in any finite | ||
| // truncation of the binary expansion. | ||
| u |= 0x8000000000000001ULL; | ||
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| // Round to double in [2^63, 2^64]. | ||
| s = static_cast<double>(u); | ||
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| // Scale into [1/2, 1]. | ||
| s *= ldexp(1, -64); | ||
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| // Apply the exponent. This is a separate step, and done with | ||
| // multiplication, because some platforms have broken ldexp. | ||
| s *= ldexp(1, -e); | ||
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| return s; | ||
| } | ||
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| } // namespace deterministic | ||
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| } // namespace random | ||
| } // namespace brave_base |
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