NS-3 based Named Data Networking (NDN) simulator
ndnSIM 2.5: NDN, CCN, CCNx, content centric networks
API Documentation
rtt-estimator.cpp
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1 /* -*- Mode:C++; c-file-style:"gnu"; indent-tabs-mode:nil; -*- */
2 /*
3  * Copyright (C) 2016-2018, Arizona Board of Regents.
4  *
5  * This file is part of ndn-cxx library (NDN C++ library with eXperimental eXtensions).
6  *
7  * ndn-cxx library is free software: you can redistribute it and/or modify it under the
8  * terms of the GNU Lesser General Public License as published by the Free Software
9  * Foundation, either version 3 of the License, or (at your option) any later version.
10  *
11  * ndn-cxx library is distributed in the hope that it will be useful, but WITHOUT ANY
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13  * PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.
14  *
15  * You should have received copies of the GNU General Public License and GNU Lesser
16  * General Public License along with ndn-cxx, e.g., in COPYING.md file. If not, see
17  * <http://www.gnu.org/licenses/>.
18  *
19  * See AUTHORS.md for complete list of ndn-cxx authors and contributors.
20  *
21  * @author Shuo Yang
22  * @author Weiwei Liu
23  * @author Chavoosh Ghasemi
24  */
25 
27 
28 #include <cmath>
29 #include <limits>
30 
31 namespace ndn {
32 namespace util {
33 
35  : m_options(options)
36  , m_sRtt(std::numeric_limits<double>::quiet_NaN())
37  , m_rttVar(std::numeric_limits<double>::quiet_NaN())
38  , m_rto(m_options.initialRto.count())
39  , m_rttMin(std::numeric_limits<double>::max())
40  , m_rttMax(std::numeric_limits<double>::min())
41  , m_rttAvg(0.0)
42  , m_nRttSamples(0)
43 {
44 }
45 
46 void
47 RttEstimator::addMeasurement(MillisecondsDouble rtt, size_t nExpectedSamples)
48 {
49  BOOST_ASSERT(nExpectedSamples > 0);
50 
51  if (m_nRttSamples == 0) { // first measurement
52  m_sRtt = rtt;
53  m_rttVar = m_sRtt / 2;
54  m_rto = m_sRtt + m_options.k * m_rttVar;
55  }
56  else {
57  double alpha = m_options.alpha / nExpectedSamples;
58  double beta = m_options.beta / nExpectedSamples;
59  m_rttVar = (1 - beta) * m_rttVar + beta * time::abs(m_sRtt - rtt);
60  m_sRtt = (1 - alpha) * m_sRtt + alpha * rtt;
61  m_rto = m_sRtt + m_options.k * m_rttVar;
62  }
63 
64  m_rto = clamp(m_rto, m_options.minRto, m_options.maxRto);
65 
66  m_rttAvg = MillisecondsDouble((m_nRttSamples * m_rttAvg.count() + rtt.count()) / (m_nRttSamples + 1));
67  m_rttMax = std::max<MillisecondsDouble>(rtt, m_rttMax);
68  m_rttMin = std::min<MillisecondsDouble>(rtt, m_rttMin);
69  m_nRttSamples++;
70 }
71 
72 void
74 {
75  m_rto = clamp(m_rto * m_options.rtoBackoffMultiplier,
76  m_options.minRto, m_options.maxRto);
77 }
78 
79 } // namespace util
80 } // namespace ndn
Copyright (c) 2011-2015 Regents of the University of California.
MillisecondsDouble minRto
lower bound of RTO
double alpha
weight of exponential moving average for meanRtt
double beta
weight of exponential moving average for varRtt
constexpr const T & clamp(const T &v, const T &lo, const T &hi, Compare comp)
Definition: backports.hpp:78
const double alpha
constexpr duration< Rep, Period > abs(duration< Rep, Period > d)
Definition: time.hpp:50
void backoffRto()
Backoff RTO by a factor of Options::rtoBackoffMultiplier.
RttEstimator(const Options &options=Options())
Create a RTT Estimator.
void addMeasurement(MillisecondsDouble rtt, size_t nExpectedSamples)
Add a new RTT measurement to the estimator.
MillisecondsDouble maxRto
upper bound of RTO
int k
factor of RTT variation when calculating RTO
time::duration< double, time::milliseconds::period > MillisecondsDouble