Davide Pesavento
60f8cc12e2
Cleanup core/common.hpp Change-Id: I6566b0224e24716691d5896462aa7613547ed950 Refs: #3076
99 lines
3.1 KiB
C++
99 lines
3.1 KiB
C++
/* -*- Mode:C++; c-file-style:"gnu"; indent-tabs-mode:nil; -*- */
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/*
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* Copyright (c) 2016-2018, Arizona Board of Regents.
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*
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* This file is part of ndn-tools (Named Data Networking Essential Tools).
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* See AUTHORS.md for complete list of ndn-tools authors and contributors.
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*
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* ndn-tools is free software: you can redistribute it and/or modify it under the terms
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* of the GNU General Public License as published by the Free Software Foundation,
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* either version 3 of the License, or (at your option) any later version.
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*
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* ndn-tools is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
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* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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* PURPOSE. See the GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License along with
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* ndn-tools, e.g., in COPYING.md file. If not, see <http://www.gnu.org/licenses/>.
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*
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* See AUTHORS.md for complete list of ndn-cxx authors and contributors.
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*
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* @author Shuo Yang
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* @author Weiwei Liu
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* @author Chavoosh Ghasemi
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*/
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#include "aimd-rtt-estimator.hpp"
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#include <cmath>
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namespace ndn {
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namespace chunks {
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namespace aimd {
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RttEstimator::RttEstimator(const Options& options)
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: m_options(options)
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, m_sRtt(std::numeric_limits<double>::quiet_NaN())
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, m_rttVar(std::numeric_limits<double>::quiet_NaN())
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, m_rto(m_options.initialRto.count())
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, m_rttMin(std::numeric_limits<double>::max())
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, m_rttMax(std::numeric_limits<double>::min())
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, m_rttAvg(0.0)
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, m_nRttSamples(0)
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{
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if (m_options.isVerbose) {
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std::cerr << m_options;
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}
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}
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void
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RttEstimator::addMeasurement(uint64_t segNo, Milliseconds rtt, size_t nExpectedSamples)
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{
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BOOST_ASSERT(nExpectedSamples > 0);
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if (m_nRttSamples == 0) { // first measurement
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m_sRtt = rtt;
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m_rttVar = m_sRtt / 2;
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m_rto = m_sRtt + m_options.k * m_rttVar;
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}
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else {
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double alpha = m_options.alpha / nExpectedSamples;
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double beta = m_options.beta / nExpectedSamples;
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m_rttVar = (1 - beta) * m_rttVar + beta * time::abs(m_sRtt - rtt);
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m_sRtt = (1 - alpha) * m_sRtt + alpha * rtt;
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m_rto = m_sRtt + m_options.k * m_rttVar;
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}
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m_rto = ndn::clamp(m_rto, m_options.minRto, m_options.maxRto);
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afterRttMeasurement({segNo, rtt, m_sRtt, m_rttVar, m_rto});
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m_rttAvg = (m_nRttSamples * m_rttAvg + rtt.count()) / (m_nRttSamples + 1);
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m_rttMax = std::max(rtt.count(), m_rttMax);
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m_rttMin = std::min(rtt.count(), m_rttMin);
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m_nRttSamples++;
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}
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void
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RttEstimator::backoffRto()
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{
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m_rto = ndn::clamp(m_rto * m_options.rtoBackoffMultiplier,
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m_options.minRto, m_options.maxRto);
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}
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std::ostream&
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operator<<(std::ostream& os, const RttEstimator::Options& options)
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{
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os << "RTT estimator parameters:\n"
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<< "\tAlpha = " << options.alpha << "\n"
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<< "\tBeta = " << options.beta << "\n"
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<< "\tK = " << options.k << "\n"
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<< "\tInitial RTO = " << options.initialRto << "\n"
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<< "\tMin RTO = " << options.minRto << "\n"
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<< "\tMax RTO = " << options.maxRto << "\n";
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return os;
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}
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} // namespace aimd
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} // namespace chunks
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} // namespace ndn
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