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/* -*- Mode:C++; c-file-style:"gnu"; indent-tabs-mode:nil; -*- */
/*
* Copyright (c) 2016-2018, Regents of the University of California,
* Colorado State University,
* University Pierre & Marie Curie, Sorbonne University.
*
* This file is part of ndn-tools (Named Data Networking Essential Tools).
* See AUTHORS.md for complete list of ndn-tools authors and contributors.
*
* ndn-tools is free software: you can redistribute it and/or modify it under the terms
* of the GNU General Public License as published by the Free Software Foundation,
* either version 3 of the License, or (at your option) any later version.
*
* ndn-tools 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License along with
* ndn-tools, e.g., in COPYING.md file. If not, see <http://www.gnu.org/licenses/>.
*
* See AUTHORS.md for complete list of ndn-cxx authors and contributors.
*
* @author Weiwei Liu
* @author Chavoosh Ghasemi
*/
#include "tools/chunks/catchunks/aimd-rtt-estimator.hpp"
#include "tests/test-common.hpp"
namespace ndn {
namespace chunks {
namespace aimd {
namespace tests {
class RttEstimatorFixture
{
protected:
RttEstimatorFixture()
: options(makeRttEstimatorOptions())
, rttEstimator(options)
{
}
private:
static RttEstimator::Options
makeRttEstimatorOptions()
{
RttEstimator::Options rttOptions;
rttOptions.alpha = 0.125;
rttOptions.beta = 0.25;
rttOptions.k = 4;
rttOptions.minRto = Milliseconds(200.0);
rttOptions.maxRto = Milliseconds(4000.0);
return rttOptions;
}
protected:
RttEstimator::Options options;
RttEstimator rttEstimator;
};
BOOST_AUTO_TEST_SUITE(Chunks)
BOOST_FIXTURE_TEST_SUITE(TestAimdRttEstimator, RttEstimatorFixture)
BOOST_AUTO_TEST_CASE(MinAvgMaxRtt)
{
// check initial values
BOOST_CHECK_CLOSE(rttEstimator.m_rttMin, std::numeric_limits<double>::max(), 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttAvg, 0.0, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttMax, std::numeric_limits<double>::min(), 0.1);
BOOST_CHECK_EQUAL(rttEstimator.m_nRttSamples, 0);
// start with three samples
rttEstimator.addMeasurement(1, Milliseconds(100), 1);
rttEstimator.addMeasurement(2, Milliseconds(400), 1);
rttEstimator.addMeasurement(3, Milliseconds(250), 1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttMin, 100, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttAvg, 250, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttMax, 400, 0.1);
BOOST_CHECK_EQUAL(rttEstimator.m_nRttSamples, 3);
// add another sample (new minimum)
rttEstimator.addMeasurement(4, Milliseconds(50), 2);
BOOST_CHECK_CLOSE(rttEstimator.m_rttMin, 50, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttAvg, 200, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttMax, 400, 0.1);
BOOST_CHECK_EQUAL(rttEstimator.m_nRttSamples, 4);
// add another sample (new maximum)
rttEstimator.addMeasurement(5, Milliseconds(700), 1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttMin, 50, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttAvg, 300, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttMax, 700, 0.1);
BOOST_CHECK_EQUAL(rttEstimator.m_nRttSamples, 5);
}
BOOST_AUTO_TEST_CASE(MeasureRtt)
{
BOOST_REQUIRE(std::isnan(rttEstimator.m_sRtt.count()));
BOOST_REQUIRE(std::isnan(rttEstimator.m_rttVar.count()));
BOOST_REQUIRE_CLOSE(rttEstimator.m_rto.count(), options.initialRto.count(), 1);
// first measurement
rttEstimator.addMeasurement(1, Milliseconds(100), 1);
BOOST_CHECK_CLOSE(rttEstimator.m_sRtt.count(), 100, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttVar.count(), 50, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 300, 0.1);
rttEstimator.m_sRtt = Milliseconds(500.0);
rttEstimator.m_rttVar = Milliseconds(100.0);
rttEstimator.m_rto = Milliseconds(900.0);
size_t nExpectedSamples = 1;
rttEstimator.addMeasurement(1, Milliseconds(100), nExpectedSamples);
BOOST_CHECK_CLOSE(rttEstimator.m_sRtt.count(), 450, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttVar.count(), 175, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 1150, 0.1);
// expected samples larger than 1
nExpectedSamples = 5;
rttEstimator.addMeasurement(1, Milliseconds(100), nExpectedSamples);
BOOST_CHECK_CLOSE(rttEstimator.m_sRtt.count(), 441.25, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttVar.count(), 183.75, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 1176.25, 0.1);
rttEstimator.m_sRtt = Milliseconds(100.0);
rttEstimator.m_rttVar = Milliseconds(30.0);
rttEstimator.m_rto = Milliseconds(220.0);
// check if minRto works
nExpectedSamples = 1;
rttEstimator.addMeasurement(1, Milliseconds(100), nExpectedSamples);
BOOST_CHECK_CLOSE(rttEstimator.m_sRtt.count(), 100, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttVar.count(), 22.5, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 200, 0.1);
rttEstimator.m_sRtt = Milliseconds(2000.0);
rttEstimator.m_rttVar = Milliseconds(400.0);
rttEstimator.m_rto = Milliseconds(3600.0);
// check if maxRto works
nExpectedSamples = 1;
rttEstimator.addMeasurement(1, Milliseconds(100), nExpectedSamples);
BOOST_CHECK_CLOSE(rttEstimator.m_sRtt.count(), 1762.5, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rttVar.count(), 775, 0.1);
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 4000, 0.1);
}
BOOST_AUTO_TEST_CASE(RtoBackoff)
{
rttEstimator.m_rto = Milliseconds(500.0);
rttEstimator.backoffRto();
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 1000, 0.1);
// check if minRto works
rttEstimator.m_rto = Milliseconds(10.0);
rttEstimator.backoffRto();
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 200, 0.1);
// check if maxRto works
rttEstimator.m_rto = Milliseconds(3000.0);
rttEstimator.backoffRto();
BOOST_CHECK_CLOSE(rttEstimator.m_rto.count(), 4000, 0.1);
}
BOOST_AUTO_TEST_SUITE_END() // TestAimdRttEstimator
BOOST_AUTO_TEST_SUITE_END() // Chunks
} // namespace tests
} // namespace aimd
} // namespace chunks
} // namespace ndn