700 lines
23 KiB
C
700 lines
23 KiB
C
/*-
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* Copyright (c) 2009-2013
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* Swinburne University of Technology, Melbourne, Australia
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* All rights reserved.
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*
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* This software was developed at the Centre for Advanced Internet
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* Architectures, Swinburne University of Technology, by David Hayes, made
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* possible in part by a gift from The Cisco University Research Program Fund,
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* a corporate advised fund of Silicon Valley Community Foundation. Development
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* and testing were further assisted by a grant from the FreeBSD Foundation.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND
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* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
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* OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
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* OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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* SUCH DAMAGE.
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*/
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/*
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* CAIA Delay-Gradient (CDG) congestion control algorithm
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*
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* An implemention of the delay-gradient congestion control algorithm proposed
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* in the following paper:
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*
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* D. A. Hayes and G. Armitage, "Revisiting TCP Congestion Control using Delay
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* Gradients", in IFIP Networking, Valencia, Spain, 9-13 May 2011.
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*
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* Developed as part of the NewTCP research project at Swinburne University of
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* Technology's Centre for Advanced Internet Architectures, Melbourne,
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* Australia. More details are available at:
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* http://caia.swin.edu.au/urp/newtcp/
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*/
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#include <sys/cdefs.h>
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__FBSDID("$FreeBSD$");
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#include <sys/param.h>
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#include <sys/hhook.h>
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#include <sys/kernel.h>
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#include <sys/khelp.h>
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#include <sys/limits.h>
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#include <sys/lock.h>
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#include <sys/malloc.h>
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#include <sys/module.h>
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#include <sys/queue.h>
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#include <sys/socket.h>
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#include <sys/socketvar.h>
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#include <sys/sysctl.h>
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#include <sys/systm.h>
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#include <net/vnet.h>
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#include <netinet/tcp.h>
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#include <netinet/tcp_seq.h>
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#include <netinet/tcp_timer.h>
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#include <netinet/tcp_var.h>
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#include <netinet/cc/cc.h>
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#include <netinet/cc/cc_module.h>
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#include <netinet/khelp/h_ertt.h>
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#include <vm/uma.h>
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#define CDG_VERSION "0.1"
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#define CAST_PTR_INT(X) (*((int*)(X)))
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/* Private delay-gradient induced congestion control signal. */
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#define CC_CDG_DELAY 0x01000000
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/* NewReno window deflation factor on loss (as a percentage). */
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#define RENO_BETA 50
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/* Queue states. */
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#define CDG_Q_EMPTY 1
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#define CDG_Q_RISING 2
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#define CDG_Q_FALLING 3
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#define CDG_Q_FULL 4
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#define CDG_Q_UNKNOWN 9999
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/* Number of bit shifts used in probexp lookup table. */
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#define EXP_PREC 15
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/* Largest gradient represented in probexp lookup table. */
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#define MAXGRAD 5
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/*
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* Delay Precision Enhance - number of bit shifts used for qtrend related
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* integer arithmetic precision.
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*/
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#define D_P_E 7
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struct qdiff_sample {
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long qdiff;
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STAILQ_ENTRY(qdiff_sample) qdiff_lnk;
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};
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struct cdg {
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long max_qtrend;
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long min_qtrend;
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STAILQ_HEAD(minrtts_head, qdiff_sample) qdiffmin_q;
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STAILQ_HEAD(maxrtts_head, qdiff_sample) qdiffmax_q;
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long window_incr;
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/* rttcount for window increase when in congestion avoidance */
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long rtt_count;
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/* maximum measured rtt within an rtt period */
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int maxrtt_in_rtt;
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/* maximum measured rtt within prev rtt period */
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int maxrtt_in_prevrtt;
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/* minimum measured rtt within an rtt period */
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int minrtt_in_rtt;
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/* minimum measured rtt within prev rtt period */
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int minrtt_in_prevrtt;
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/* consecutive congestion episode counter */
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uint32_t consec_cong_cnt;
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/* when tracking a new reno type loss window */
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uint32_t shadow_w;
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/* maximum number of samples in the moving average queue */
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int sample_q_size;
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/* number of samples in the moving average queue */
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int num_samples;
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/* estimate of the queue state of the path */
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int queue_state;
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};
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/*
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* Lookup table for:
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* (1 - exp(-x)) << EXP_PREC, where x = [0,MAXGRAD] in 2^-7 increments
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*
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* Note: probexp[0] is set to 10 (not 0) as a safety for very low increase
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* gradients.
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*/
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static const int probexp[641] = {
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10,255,508,759,1008,1255,1501,1744,1985,2225,2463,2698,2932,3165,3395,3624,
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3850,4075,4299,4520,4740,4958,5175,5389,5602,5814,6024,6232,6438,6643,6846,
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7048,7248,7447,7644,7839,8033,8226,8417,8606,8794,8981,9166,9350,9532,9713,
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9892,10070,10247,10422,10596,10769,10940,11110,11278,11445,11611,11776,11939,
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12101,12262,12422,12580,12737,12893,13048,13201,13354,13505,13655,13803,13951,
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14097,14243,14387,14530,14672,14813,14952,15091,15229,15365,15500,15635,15768,
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15900,16032,16162,16291,16419,16547,16673,16798,16922,17046,17168,17289,17410,
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17529,17648,17766,17882,17998,18113,18227,18340,18453,18564,18675,18784,18893,
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19001,19108,19215,19320,19425,19529,19632,19734,19835,19936,20036,20135,20233,
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20331,20427,20523,20619,20713,20807,20900,20993,21084,21175,21265,21355,21444,
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21532,21619,21706,21792,21878,21962,22046,22130,22213,22295,22376,22457,22537,
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22617,22696,22774,22852,22929,23006,23082,23157,23232,23306,23380,23453,23525,
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23597,23669,23739,23810,23879,23949,24017,24085,24153,24220,24286,24352,24418,
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24483,24547,24611,24675,24738,24800,24862,24924,24985,25045,25106,25165,25224,
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25283,25341,25399,25456,25513,25570,25626,25681,25737,25791,25846,25899,25953,
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26006,26059,26111,26163,26214,26265,26316,26366,26416,26465,26514,26563,26611,
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26659,26707,26754,26801,26847,26893,26939,26984,27029,27074,27118,27162,27206,
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27249,27292,27335,27377,27419,27460,27502,27543,27583,27624,27664,27703,27743,
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27782,27821,27859,27897,27935,27973,28010,28047,28084,28121,28157,28193,28228,
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28263,28299,28333,28368,28402,28436,28470,28503,28536,28569,28602,28634,28667,
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28699,28730,28762,28793,28824,28854,28885,28915,28945,28975,29004,29034,29063,
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29092,29120,29149,29177,29205,29232,29260,29287,29314,29341,29368,29394,29421,
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29447,29472,29498,29524,29549,29574,29599,29623,29648,29672,29696,29720,29744,
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29767,29791,29814,29837,29860,29882,29905,29927,29949,29971,29993,30014,30036,
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30057,30078,30099,30120,30141,30161,30181,30201,30221,30241,30261,30280,30300,
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30319,30338,30357,30376,30394,30413,30431,30449,30467,30485,30503,30521,30538,
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30555,30573,30590,30607,30624,30640,30657,30673,30690,30706,30722,30738,30753,
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30769,30785,30800,30815,30831,30846,30861,30876,30890,30905,30919,30934,30948,
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30962,30976,30990,31004,31018,31031,31045,31058,31072,31085,31098,31111,31124,
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31137,31149,31162,31174,31187,31199,31211,31223,31235,31247,31259,31271,31283,
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31294,31306,31317,31328,31339,31351,31362,31373,31383,31394,31405,31416,31426,
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31436,31447,31457,31467,31477,31487,31497,31507,31517,31527,31537,31546,31556,
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31565,31574,31584,31593,31602,31611,31620,31629,31638,31647,31655,31664,31673,
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31681,31690,31698,31706,31715,31723,31731,31739,31747,31755,31763,31771,31778,
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31786,31794,31801,31809,31816,31824,31831,31838,31846,31853,31860,31867,31874,
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31881,31888,31895,31902,31908,31915,31922,31928,31935,31941,31948,31954,31960,
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31967,31973,31979,31985,31991,31997,32003,32009,32015,32021,32027,32033,32038,
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32044,32050,32055,32061,32066,32072,32077,32083,32088,32093,32098,32104,32109,
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32114,32119,32124,32129,32134,32139,32144,32149,32154,32158,32163,32168,32173,
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32177,32182,32186,32191,32195,32200,32204,32209,32213,32217,32222,32226,32230,
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32234,32238,32242,32247,32251,32255,32259,32263,32267,32270,32274,32278,32282,
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32286,32290,32293,32297,32301,32304,32308,32311,32315,32318,32322,32325,32329,
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32332,32336,32339,32342,32346,32349,32352,32356,32359,32362,32365,32368,32371,
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32374,32377,32381,32384,32387,32389,32392,32395,32398,32401,32404,32407,32410,
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32412,32415,32418,32421,32423,32426,32429,32431,32434,32437,32439,32442,32444,
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32447,32449,32452,32454,32457,32459,32461,32464,32466,32469,32471,32473,32476,
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32478,32480,32482,32485,32487,32489,32491,32493,32495,32497,32500,32502,32504,
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32506,32508,32510,32512,32514,32516,32518,32520,32522,32524,32526,32527,32529,
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32531,32533,32535,32537,32538,32540,32542,32544,32545,32547};
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static uma_zone_t qdiffsample_zone;
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static MALLOC_DEFINE(M_CDG, "cdg data",
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"Per connection data required for the CDG congestion control algorithm");
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static int ertt_id;
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static VNET_DEFINE(uint32_t, cdg_alpha_inc);
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static VNET_DEFINE(uint32_t, cdg_beta_delay);
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static VNET_DEFINE(uint32_t, cdg_beta_loss);
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static VNET_DEFINE(uint32_t, cdg_smoothing_factor);
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static VNET_DEFINE(uint32_t, cdg_exp_backoff_scale);
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static VNET_DEFINE(uint32_t, cdg_consec_cong);
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static VNET_DEFINE(uint32_t, cdg_hold_backoff);
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#define V_cdg_alpha_inc VNET(cdg_alpha_inc)
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#define V_cdg_beta_delay VNET(cdg_beta_delay)
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#define V_cdg_beta_loss VNET(cdg_beta_loss)
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#define V_cdg_smoothing_factor VNET(cdg_smoothing_factor)
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#define V_cdg_exp_backoff_scale VNET(cdg_exp_backoff_scale)
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#define V_cdg_consec_cong VNET(cdg_consec_cong)
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#define V_cdg_hold_backoff VNET(cdg_hold_backoff)
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/* Function prototypes. */
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static int cdg_mod_init(void);
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static int cdg_mod_destroy(void);
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static void cdg_conn_init(struct cc_var *ccv);
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static int cdg_cb_init(struct cc_var *ccv);
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static void cdg_cb_destroy(struct cc_var *ccv);
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static void cdg_cong_signal(struct cc_var *ccv, uint32_t signal_type);
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static void cdg_ack_received(struct cc_var *ccv, uint16_t ack_type);
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struct cc_algo cdg_cc_algo = {
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.name = "cdg",
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.mod_init = cdg_mod_init,
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.ack_received = cdg_ack_received,
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.cb_destroy = cdg_cb_destroy,
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.cb_init = cdg_cb_init,
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.conn_init = cdg_conn_init,
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.cong_signal = cdg_cong_signal,
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.mod_destroy = cdg_mod_destroy
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};
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/* Vnet created and being initialised. */
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static void
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cdg_init_vnet(const void *unused __unused)
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{
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V_cdg_alpha_inc = 0;
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V_cdg_beta_delay = 70;
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V_cdg_beta_loss = 50;
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V_cdg_smoothing_factor = 8;
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V_cdg_exp_backoff_scale = 3;
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V_cdg_consec_cong = 5;
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V_cdg_hold_backoff = 5;
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}
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static int
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cdg_mod_init(void)
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{
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VNET_ITERATOR_DECL(v);
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ertt_id = khelp_get_id("ertt");
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if (ertt_id <= 0)
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return (EINVAL);
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qdiffsample_zone = uma_zcreate("cdg_qdiffsample",
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sizeof(struct qdiff_sample), NULL, NULL, NULL, NULL, 0, 0);
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VNET_LIST_RLOCK();
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VNET_FOREACH(v) {
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CURVNET_SET(v);
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cdg_init_vnet(NULL);
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CURVNET_RESTORE();
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}
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VNET_LIST_RUNLOCK();
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cdg_cc_algo.post_recovery = newreno_cc_algo.post_recovery;
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cdg_cc_algo.after_idle = newreno_cc_algo.after_idle;
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return (0);
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}
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static int
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cdg_mod_destroy(void)
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{
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uma_zdestroy(qdiffsample_zone);
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return (0);
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}
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static int
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cdg_cb_init(struct cc_var *ccv)
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{
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struct cdg *cdg_data;
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cdg_data = malloc(sizeof(struct cdg), M_CDG, M_NOWAIT);
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if (cdg_data == NULL)
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return (ENOMEM);
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cdg_data->shadow_w = 0;
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cdg_data->max_qtrend = 0;
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cdg_data->min_qtrend = 0;
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cdg_data->queue_state = CDG_Q_UNKNOWN;
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cdg_data->maxrtt_in_rtt = 0;
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cdg_data->maxrtt_in_prevrtt = 0;
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cdg_data->minrtt_in_rtt = INT_MAX;
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cdg_data->minrtt_in_prevrtt = 0;
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cdg_data->window_incr = 0;
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cdg_data->rtt_count = 0;
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cdg_data->consec_cong_cnt = 0;
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cdg_data->sample_q_size = V_cdg_smoothing_factor;
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cdg_data->num_samples = 0;
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STAILQ_INIT(&cdg_data->qdiffmin_q);
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STAILQ_INIT(&cdg_data->qdiffmax_q);
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ccv->cc_data = cdg_data;
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return (0);
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}
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static void
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cdg_conn_init(struct cc_var *ccv)
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{
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struct cdg *cdg_data = ccv->cc_data;
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/*
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* Initialise the shadow_cwnd in case we are competing with loss based
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* flows from the start
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*/
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cdg_data->shadow_w = CCV(ccv, snd_cwnd);
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}
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static void
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cdg_cb_destroy(struct cc_var *ccv)
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{
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struct cdg *cdg_data;
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struct qdiff_sample *qds, *qds_n;
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cdg_data = ccv->cc_data;
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qds = STAILQ_FIRST(&cdg_data->qdiffmin_q);
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while (qds != NULL) {
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qds_n = STAILQ_NEXT(qds, qdiff_lnk);
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uma_zfree(qdiffsample_zone,qds);
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qds = qds_n;
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}
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qds = STAILQ_FIRST(&cdg_data->qdiffmax_q);
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while (qds != NULL) {
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qds_n = STAILQ_NEXT(qds, qdiff_lnk);
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uma_zfree(qdiffsample_zone,qds);
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qds = qds_n;
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}
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free(ccv->cc_data, M_CDG);
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}
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static int
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cdg_beta_handler(SYSCTL_HANDLER_ARGS)
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{
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if (req->newptr != NULL &&
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(CAST_PTR_INT(req->newptr) == 0 || CAST_PTR_INT(req->newptr) > 100))
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return (EINVAL);
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return (sysctl_handle_int(oidp, arg1, arg2, req));
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}
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static int
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cdg_exp_backoff_scale_handler(SYSCTL_HANDLER_ARGS)
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{
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if (req->newptr != NULL && CAST_PTR_INT(req->newptr) < 1)
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return (EINVAL);
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return (sysctl_handle_int(oidp, arg1, arg2, req));
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}
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static inline unsigned long
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cdg_window_decrease(struct cc_var *ccv, unsigned long owin, unsigned int beta)
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{
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return ((ulmin(CCV(ccv, snd_wnd), owin) * beta) / 100);
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}
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/*
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* Window increase function
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* This window increase function is independent of the initial window size
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* to ensure small window flows are not discriminated against (i.e. fairness).
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* It increases at 1pkt/rtt like Reno for alpha_inc rtts, and then 2pkts/rtt for
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* the next alpha_inc rtts, etc.
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*/
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static void
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cdg_window_increase(struct cc_var *ccv, int new_measurement)
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{
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struct cdg *cdg_data;
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int incr, s_w_incr;
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cdg_data = ccv->cc_data;
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incr = s_w_incr = 0;
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|
if (CCV(ccv, snd_cwnd) <= CCV(ccv, snd_ssthresh)) {
|
|
/* Slow start. */
|
|
incr = CCV(ccv, t_maxseg);
|
|
s_w_incr = incr;
|
|
cdg_data->window_incr = cdg_data->rtt_count = 0;
|
|
} else {
|
|
/* Congestion avoidance. */
|
|
if (new_measurement) {
|
|
s_w_incr = CCV(ccv, t_maxseg);
|
|
if (V_cdg_alpha_inc == 0) {
|
|
incr = CCV(ccv, t_maxseg);
|
|
} else {
|
|
if (++cdg_data->rtt_count >= V_cdg_alpha_inc) {
|
|
cdg_data->window_incr++;
|
|
cdg_data->rtt_count = 0;
|
|
}
|
|
incr = CCV(ccv, t_maxseg) *
|
|
cdg_data->window_incr;
|
|
}
|
|
}
|
|
}
|
|
|
|
if (cdg_data->shadow_w > 0)
|
|
cdg_data->shadow_w = ulmin(cdg_data->shadow_w + s_w_incr,
|
|
TCP_MAXWIN << CCV(ccv, snd_scale));
|
|
|
|
CCV(ccv, snd_cwnd) = ulmin(CCV(ccv, snd_cwnd) + incr,
|
|
TCP_MAXWIN << CCV(ccv, snd_scale));
|
|
}
|
|
|
|
static void
|
|
cdg_cong_signal(struct cc_var *ccv, uint32_t signal_type)
|
|
{
|
|
struct cdg *cdg_data = ccv->cc_data;
|
|
|
|
switch(signal_type) {
|
|
case CC_CDG_DELAY:
|
|
CCV(ccv, snd_ssthresh) = cdg_window_decrease(ccv,
|
|
CCV(ccv, snd_cwnd), V_cdg_beta_delay);
|
|
CCV(ccv, snd_cwnd) = CCV(ccv, snd_ssthresh);
|
|
CCV(ccv, snd_recover) = CCV(ccv, snd_max);
|
|
cdg_data->window_incr = cdg_data->rtt_count = 0;
|
|
ENTER_CONGRECOVERY(CCV(ccv, t_flags));
|
|
break;
|
|
case CC_NDUPACK:
|
|
/*
|
|
* If already responding to congestion OR we have guessed no
|
|
* queue in the path is full.
|
|
*/
|
|
if (IN_CONGRECOVERY(CCV(ccv, t_flags)) ||
|
|
cdg_data->queue_state < CDG_Q_FULL) {
|
|
CCV(ccv, snd_ssthresh) = CCV(ccv, snd_cwnd);
|
|
CCV(ccv, snd_recover) = CCV(ccv, snd_max);
|
|
} else {
|
|
/*
|
|
* Loss is likely to be congestion related. We have
|
|
* inferred a queue full state, so have shadow window
|
|
* react to loss as NewReno would.
|
|
*/
|
|
if (cdg_data->shadow_w > 0)
|
|
cdg_data->shadow_w = cdg_window_decrease(ccv,
|
|
cdg_data->shadow_w, RENO_BETA);
|
|
|
|
CCV(ccv, snd_ssthresh) = ulmax(cdg_data->shadow_w,
|
|
cdg_window_decrease(ccv, CCV(ccv, snd_cwnd),
|
|
V_cdg_beta_loss));
|
|
|
|
cdg_data->window_incr = cdg_data->rtt_count = 0;
|
|
}
|
|
ENTER_RECOVERY(CCV(ccv, t_flags));
|
|
break;
|
|
default:
|
|
newreno_cc_algo.cong_signal(ccv, signal_type);
|
|
break;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Using a negative exponential probabilistic backoff so that sources with
|
|
* varying RTTs which share the same link will, on average, have the same
|
|
* probability of backoff over time.
|
|
*
|
|
* Prob_backoff = 1 - exp(-qtrend / V_cdg_exp_backoff_scale), where
|
|
* V_cdg_exp_backoff_scale is the average qtrend for the exponential backoff.
|
|
*/
|
|
static inline int
|
|
prob_backoff(long qtrend)
|
|
{
|
|
int backoff, idx, p;
|
|
|
|
backoff = (qtrend > ((MAXGRAD * V_cdg_exp_backoff_scale) << D_P_E));
|
|
|
|
if (!backoff) {
|
|
if (V_cdg_exp_backoff_scale > 1)
|
|
idx = (qtrend + V_cdg_exp_backoff_scale / 2) /
|
|
V_cdg_exp_backoff_scale;
|
|
else
|
|
idx = qtrend;
|
|
|
|
/* Backoff probability proportional to rate of queue growth. */
|
|
p = (INT_MAX / (1 << EXP_PREC)) * probexp[idx];
|
|
backoff = (random() < p);
|
|
}
|
|
|
|
return (backoff);
|
|
}
|
|
|
|
static inline void
|
|
calc_moving_average(struct cdg *cdg_data, long qdiff_max, long qdiff_min)
|
|
{
|
|
struct qdiff_sample *qds;
|
|
|
|
++cdg_data->num_samples;
|
|
if (cdg_data->num_samples > cdg_data->sample_q_size) {
|
|
/* Minimum RTT. */
|
|
qds = STAILQ_FIRST(&cdg_data->qdiffmin_q);
|
|
cdg_data->min_qtrend = cdg_data->min_qtrend +
|
|
(qdiff_min - qds->qdiff) / cdg_data->sample_q_size;
|
|
STAILQ_REMOVE_HEAD(&cdg_data->qdiffmin_q, qdiff_lnk);
|
|
qds->qdiff = qdiff_min;
|
|
STAILQ_INSERT_TAIL(&cdg_data->qdiffmin_q, qds, qdiff_lnk);
|
|
|
|
/* Maximum RTT. */
|
|
qds = STAILQ_FIRST(&cdg_data->qdiffmax_q);
|
|
cdg_data->max_qtrend = cdg_data->max_qtrend +
|
|
(qdiff_max - qds->qdiff) / cdg_data->sample_q_size;
|
|
STAILQ_REMOVE_HEAD(&cdg_data->qdiffmax_q, qdiff_lnk);
|
|
qds->qdiff = qdiff_max;
|
|
STAILQ_INSERT_TAIL(&cdg_data->qdiffmax_q, qds, qdiff_lnk);
|
|
--cdg_data->num_samples;
|
|
} else {
|
|
qds = uma_zalloc(qdiffsample_zone, M_NOWAIT);
|
|
if (qds != NULL) {
|
|
cdg_data->min_qtrend = cdg_data->min_qtrend +
|
|
qdiff_min / cdg_data->sample_q_size;
|
|
qds->qdiff = qdiff_min;
|
|
STAILQ_INSERT_TAIL(&cdg_data->qdiffmin_q, qds,
|
|
qdiff_lnk);
|
|
}
|
|
|
|
qds = uma_zalloc(qdiffsample_zone, M_NOWAIT);
|
|
if (qds) {
|
|
cdg_data->max_qtrend = cdg_data->max_qtrend +
|
|
qdiff_max / cdg_data->sample_q_size;
|
|
qds->qdiff = qdiff_max;
|
|
STAILQ_INSERT_TAIL(&cdg_data->qdiffmax_q, qds,
|
|
qdiff_lnk);
|
|
}
|
|
}
|
|
}
|
|
|
|
static void
|
|
cdg_ack_received(struct cc_var *ccv, uint16_t ack_type)
|
|
{
|
|
struct cdg *cdg_data;
|
|
struct ertt *e_t;
|
|
long qdiff_max, qdiff_min;
|
|
int congestion, new_measurement, slowstart;
|
|
|
|
cdg_data = ccv->cc_data;
|
|
e_t = (struct ertt *)khelp_get_osd(CCV(ccv, osd), ertt_id);
|
|
new_measurement = e_t->flags & ERTT_NEW_MEASUREMENT;
|
|
congestion = 0;
|
|
cdg_data->maxrtt_in_rtt = imax(e_t->rtt, cdg_data->maxrtt_in_rtt);
|
|
cdg_data->minrtt_in_rtt = imin(e_t->rtt, cdg_data->minrtt_in_rtt);
|
|
|
|
if (new_measurement) {
|
|
slowstart = (CCV(ccv, snd_cwnd) <= CCV(ccv, snd_ssthresh));
|
|
/*
|
|
* Update smoothed gradient measurements. Since we are only
|
|
* using one measurement per RTT, use max or min rtt_in_rtt.
|
|
* This is also less noisy than a sample RTT measurement. Max
|
|
* RTT measurements can have trouble due to OS issues.
|
|
*/
|
|
if (cdg_data->maxrtt_in_prevrtt) {
|
|
qdiff_max = ((long)(cdg_data->maxrtt_in_rtt -
|
|
cdg_data->maxrtt_in_prevrtt) << D_P_E );
|
|
qdiff_min = ((long)(cdg_data->minrtt_in_rtt -
|
|
cdg_data->minrtt_in_prevrtt) << D_P_E );
|
|
|
|
calc_moving_average(cdg_data, qdiff_max, qdiff_min);
|
|
|
|
/* Probabilistic backoff with respect to gradient. */
|
|
if (slowstart && qdiff_min > 0)
|
|
congestion = prob_backoff(qdiff_min);
|
|
else if (cdg_data->min_qtrend > 0)
|
|
congestion = prob_backoff(cdg_data->min_qtrend);
|
|
else if (slowstart && qdiff_max > 0)
|
|
congestion = prob_backoff(qdiff_max);
|
|
else if (cdg_data->max_qtrend > 0)
|
|
congestion = prob_backoff(cdg_data->max_qtrend);
|
|
|
|
/* Update estimate of queue state. */
|
|
if (cdg_data->min_qtrend > 0 &&
|
|
cdg_data->max_qtrend <= 0) {
|
|
cdg_data->queue_state = CDG_Q_FULL;
|
|
} else if (cdg_data->min_qtrend >= 0 &&
|
|
cdg_data->max_qtrend < 0) {
|
|
cdg_data->queue_state = CDG_Q_EMPTY;
|
|
cdg_data->shadow_w = 0;
|
|
} else if (cdg_data->min_qtrend > 0 &&
|
|
cdg_data->max_qtrend > 0) {
|
|
cdg_data->queue_state = CDG_Q_RISING;
|
|
} else if (cdg_data->min_qtrend < 0 &&
|
|
cdg_data->max_qtrend < 0) {
|
|
cdg_data->queue_state = CDG_Q_FALLING;
|
|
}
|
|
|
|
if (cdg_data->min_qtrend < 0 ||
|
|
cdg_data->max_qtrend < 0)
|
|
cdg_data->consec_cong_cnt = 0;
|
|
}
|
|
|
|
cdg_data->minrtt_in_prevrtt = cdg_data->minrtt_in_rtt;
|
|
cdg_data->minrtt_in_rtt = INT_MAX;
|
|
cdg_data->maxrtt_in_prevrtt = cdg_data->maxrtt_in_rtt;
|
|
cdg_data->maxrtt_in_rtt = 0;
|
|
e_t->flags &= ~ERTT_NEW_MEASUREMENT;
|
|
}
|
|
|
|
if (congestion) {
|
|
cdg_data->consec_cong_cnt++;
|
|
if (!IN_RECOVERY(CCV(ccv, t_flags))) {
|
|
if (cdg_data->consec_cong_cnt <= V_cdg_consec_cong)
|
|
cdg_cong_signal(ccv, CC_CDG_DELAY);
|
|
else
|
|
/*
|
|
* We have been backing off but the queue is not
|
|
* falling. Assume we are competing with
|
|
* loss-based flows and don't back off for the
|
|
* next V_cdg_hold_backoff RTT periods.
|
|
*/
|
|
if (cdg_data->consec_cong_cnt >=
|
|
V_cdg_consec_cong + V_cdg_hold_backoff)
|
|
cdg_data->consec_cong_cnt = 0;
|
|
|
|
/* Won't see effect until 2nd RTT. */
|
|
cdg_data->maxrtt_in_prevrtt = 0;
|
|
/*
|
|
* Resync shadow window in case we are competing with a
|
|
* loss based flow
|
|
*/
|
|
cdg_data->shadow_w = ulmax(CCV(ccv, snd_cwnd),
|
|
cdg_data->shadow_w);
|
|
}
|
|
} else if (ack_type == CC_ACK)
|
|
cdg_window_increase(ccv, new_measurement);
|
|
}
|
|
|
|
/* When a vnet is created and being initialised, init the per-stack CDG vars. */
|
|
VNET_SYSINIT(cdg_init_vnet, SI_SUB_PROTO_BEGIN, SI_ORDER_FIRST,
|
|
cdg_init_vnet, NULL);
|
|
|
|
SYSCTL_DECL(_net_inet_tcp_cc_cdg);
|
|
SYSCTL_NODE(_net_inet_tcp_cc, OID_AUTO, cdg, CTLFLAG_RW, NULL,
|
|
"CAIA delay-gradient congestion control related settings");
|
|
|
|
SYSCTL_STRING(_net_inet_tcp_cc_cdg, OID_AUTO, version,
|
|
CTLFLAG_RD, CDG_VERSION, sizeof(CDG_VERSION) - 1,
|
|
"Current algorithm/implementation version number");
|
|
|
|
SYSCTL_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, alpha_inc,
|
|
CTLFLAG_VNET | CTLFLAG_RW, &VNET_NAME(cdg_alpha_inc), 0,
|
|
"Increment the window increase factor alpha by 1 MSS segment every "
|
|
"alpha_inc RTTs during congestion avoidance mode.");
|
|
|
|
SYSCTL_PROC(_net_inet_tcp_cc_cdg, OID_AUTO, beta_delay,
|
|
CTLFLAG_VNET | CTLTYPE_UINT | CTLFLAG_RW, &VNET_NAME(cdg_beta_delay), 70,
|
|
&cdg_beta_handler, "IU",
|
|
"Delay-based window decrease factor as a percentage "
|
|
"(on delay-based backoff, w = w * beta_delay / 100)");
|
|
|
|
SYSCTL_PROC(_net_inet_tcp_cc_cdg, OID_AUTO, beta_loss,
|
|
CTLFLAG_VNET | CTLTYPE_UINT | CTLFLAG_RW, &VNET_NAME(cdg_beta_loss), 50,
|
|
&cdg_beta_handler, "IU",
|
|
"Loss-based window decrease factor as a percentage "
|
|
"(on loss-based backoff, w = w * beta_loss / 100)");
|
|
|
|
SYSCTL_PROC(_net_inet_tcp_cc_cdg, OID_AUTO, exp_backoff_scale,
|
|
CTLFLAG_VNET | CTLTYPE_UINT | CTLFLAG_RW,
|
|
&VNET_NAME(cdg_exp_backoff_scale), 2, &cdg_exp_backoff_scale_handler, "IU",
|
|
"Scaling parameter for the probabilistic exponential backoff");
|
|
|
|
SYSCTL_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, smoothing_factor,
|
|
CTLFLAG_VNET | CTLFLAG_RW, &VNET_NAME(cdg_smoothing_factor), 8,
|
|
"Number of samples used for moving average smoothing (0 = no smoothing)");
|
|
|
|
SYSCTL_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, loss_compete_consec_cong,
|
|
CTLFLAG_VNET | CTLFLAG_RW, &VNET_NAME(cdg_consec_cong), 5,
|
|
"Number of consecutive delay-gradient based congestion episodes which will "
|
|
"trigger loss based CC compatibility");
|
|
|
|
SYSCTL_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, loss_compete_hold_backoff,
|
|
CTLFLAG_VNET | CTLFLAG_RW, &VNET_NAME(cdg_hold_backoff), 5,
|
|
"Number of consecutive delay-gradient based congestion episodes to hold "
|
|
"the window backoff for loss based CC compatibility");
|
|
|
|
DECLARE_CC_MODULE(cdg, &cdg_cc_algo);
|
|
|
|
MODULE_DEPEND(cdg, ertt, 1, 1, 1);
|