cc_cdg.c revision 296373
1/*- 2 * Copyright (c) 2009-2013 3 * Swinburne University of Technology, Melbourne, Australia 4 * All rights reserved. 5 * 6 * This software was developed at the Centre for Advanced Internet 7 * Architectures, Swinburne University of Technology, by David Hayes, made 8 * possible in part by a gift from The Cisco University Research Program Fund, 9 * a corporate advised fund of Silicon Valley Community Foundation. Development 10 * and testing were further assisted by a grant from the FreeBSD Foundation. 11 * 12 * Redistribution and use in source and binary forms, with or without 13 * modification, are permitted provided that the following conditions 14 * are met: 15 * 1. Redistributions of source code must retain the above copyright 16 * notice, this list of conditions and the following disclaimer. 17 * 2. Redistributions in binary form must reproduce the above copyright 18 * notice, this list of conditions and the following disclaimer in the 19 * documentation and/or other materials provided with the distribution. 20 * 21 * THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND 22 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 23 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 24 * ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE 25 * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL 26 * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS 27 * OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) 28 * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 29 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY 30 * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF 31 * SUCH DAMAGE. 32 */ 33 34/* 35 * CAIA Delay-Gradient (CDG) congestion control algorithm 36 * 37 * An implemention of the delay-gradient congestion control algorithm proposed 38 * in the following paper: 39 * 40 * D. A. Hayes and G. Armitage, "Revisiting TCP Congestion Control using Delay 41 * Gradients", in IFIP Networking, Valencia, Spain, 9-13 May 2011. 42 * 43 * Developed as part of the NewTCP research project at Swinburne University of 44 * Technology's Centre for Advanced Internet Architectures, Melbourne, 45 * Australia. More details are available at: 46 * http://caia.swin.edu.au/urp/newtcp/ 47 */ 48 49#include <sys/cdefs.h> 50__FBSDID("$FreeBSD: releng/10.3/sys/netinet/cc/cc_cdg.c 271690 2014-09-16 21:26:24Z lstewart $"); 51 52#include <sys/param.h> 53#include <sys/hhook.h> 54#include <sys/kernel.h> 55#include <sys/khelp.h> 56#include <sys/limits.h> 57#include <sys/lock.h> 58#include <sys/malloc.h> 59#include <sys/module.h> 60#include <sys/queue.h> 61#include <sys/socket.h> 62#include <sys/socketvar.h> 63#include <sys/sysctl.h> 64#include <sys/systm.h> 65 66#include <net/if.h> 67#include <net/vnet.h> 68 69#include <netinet/cc.h> 70#include <netinet/tcp_seq.h> 71#include <netinet/tcp_timer.h> 72#include <netinet/tcp_var.h> 73 74#include <netinet/cc/cc_module.h> 75 76#include <netinet/khelp/h_ertt.h> 77 78#include <vm/uma.h> 79 80#define CDG_VERSION "0.1" 81 82#define CAST_PTR_INT(X) (*((int*)(X))) 83 84/* Private delay-gradient induced congestion control signal. */ 85#define CC_CDG_DELAY 0x01000000 86 87/* NewReno window deflation factor on loss (as a percentage). */ 88#define RENO_BETA 50 89 90/* Queue states. */ 91#define CDG_Q_EMPTY 1 92#define CDG_Q_RISING 2 93#define CDG_Q_FALLING 3 94#define CDG_Q_FULL 4 95#define CDG_Q_UNKNOWN 9999 96 97/* Number of bit shifts used in probexp lookup table. */ 98#define EXP_PREC 15 99 100/* Largest gradient represented in probexp lookup table. */ 101#define MAXGRAD 5 102 103/* 104 * Delay Precision Enhance - number of bit shifts used for qtrend related 105 * integer arithmetic precision. 106 */ 107#define D_P_E 7 108 109struct qdiff_sample { 110 long qdiff; 111 STAILQ_ENTRY(qdiff_sample) qdiff_lnk; 112}; 113 114struct cdg { 115 long max_qtrend; 116 long min_qtrend; 117 STAILQ_HEAD(minrtts_head, qdiff_sample) qdiffmin_q; 118 STAILQ_HEAD(maxrtts_head, qdiff_sample) qdiffmax_q; 119 long window_incr; 120 /* rttcount for window increase when in congestion avoidance */ 121 long rtt_count; 122 /* maximum measured rtt within an rtt period */ 123 int maxrtt_in_rtt; 124 /* maximum measured rtt within prev rtt period */ 125 int maxrtt_in_prevrtt; 126 /* minimum measured rtt within an rtt period */ 127 int minrtt_in_rtt; 128 /* minimum measured rtt within prev rtt period */ 129 int minrtt_in_prevrtt; 130 /* consecutive congestion episode counter */ 131 uint32_t consec_cong_cnt; 132 /* when tracking a new reno type loss window */ 133 uint32_t shadow_w; 134 /* maximum number of samples in the moving average queue */ 135 int sample_q_size; 136 /* number of samples in the moving average queue */ 137 int num_samples; 138 /* estimate of the queue state of the path */ 139 int queue_state; 140}; 141 142/* 143 * Lookup table for: 144 * (1 - exp(-x)) << EXP_PREC, where x = [0,MAXGRAD] in 2^-7 increments 145 * 146 * Note: probexp[0] is set to 10 (not 0) as a safety for very low increase 147 * gradients. 148 */ 149static const int probexp[641] = { 150 10,255,508,759,1008,1255,1501,1744,1985,2225,2463,2698,2932,3165,3395,3624, 151 3850,4075,4299,4520,4740,4958,5175,5389,5602,5814,6024,6232,6438,6643,6846, 152 7048,7248,7447,7644,7839,8033,8226,8417,8606,8794,8981,9166,9350,9532,9713, 153 9892,10070,10247,10422,10596,10769,10940,11110,11278,11445,11611,11776,11939, 154 12101,12262,12422,12580,12737,12893,13048,13201,13354,13505,13655,13803,13951, 155 14097,14243,14387,14530,14672,14813,14952,15091,15229,15365,15500,15635,15768, 156 15900,16032,16162,16291,16419,16547,16673,16798,16922,17046,17168,17289,17410, 157 17529,17648,17766,17882,17998,18113,18227,18340,18453,18564,18675,18784,18893, 158 19001,19108,19215,19320,19425,19529,19632,19734,19835,19936,20036,20135,20233, 159 20331,20427,20523,20619,20713,20807,20900,20993,21084,21175,21265,21355,21444, 160 21532,21619,21706,21792,21878,21962,22046,22130,22213,22295,22376,22457,22537, 161 22617,22696,22774,22852,22929,23006,23082,23157,23232,23306,23380,23453,23525, 162 23597,23669,23739,23810,23879,23949,24017,24085,24153,24220,24286,24352,24418, 163 24483,24547,24611,24675,24738,24800,24862,24924,24985,25045,25106,25165,25224, 164 25283,25341,25399,25456,25513,25570,25626,25681,25737,25791,25846,25899,25953, 165 26006,26059,26111,26163,26214,26265,26316,26366,26416,26465,26514,26563,26611, 166 26659,26707,26754,26801,26847,26893,26939,26984,27029,27074,27118,27162,27206, 167 27249,27292,27335,27377,27419,27460,27502,27543,27583,27624,27664,27703,27743, 168 27782,27821,27859,27897,27935,27973,28010,28047,28084,28121,28157,28193,28228, 169 28263,28299,28333,28368,28402,28436,28470,28503,28536,28569,28602,28634,28667, 170 28699,28730,28762,28793,28824,28854,28885,28915,28945,28975,29004,29034,29063, 171 29092,29120,29149,29177,29205,29232,29260,29287,29314,29341,29368,29394,29421, 172 29447,29472,29498,29524,29549,29574,29599,29623,29648,29672,29696,29720,29744, 173 29767,29791,29814,29837,29860,29882,29905,29927,29949,29971,29993,30014,30036, 174 30057,30078,30099,30120,30141,30161,30181,30201,30221,30241,30261,30280,30300, 175 30319,30338,30357,30376,30394,30413,30431,30449,30467,30485,30503,30521,30538, 176 30555,30573,30590,30607,30624,30640,30657,30673,30690,30706,30722,30738,30753, 177 30769,30785,30800,30815,30831,30846,30861,30876,30890,30905,30919,30934,30948, 178 30962,30976,30990,31004,31018,31031,31045,31058,31072,31085,31098,31111,31124, 179 31137,31149,31162,31174,31187,31199,31211,31223,31235,31247,31259,31271,31283, 180 31294,31306,31317,31328,31339,31351,31362,31373,31383,31394,31405,31416,31426, 181 31436,31447,31457,31467,31477,31487,31497,31507,31517,31527,31537,31546,31556, 182 31565,31574,31584,31593,31602,31611,31620,31629,31638,31647,31655,31664,31673, 183 31681,31690,31698,31706,31715,31723,31731,31739,31747,31755,31763,31771,31778, 184 31786,31794,31801,31809,31816,31824,31831,31838,31846,31853,31860,31867,31874, 185 31881,31888,31895,31902,31908,31915,31922,31928,31935,31941,31948,31954,31960, 186 31967,31973,31979,31985,31991,31997,32003,32009,32015,32021,32027,32033,32038, 187 32044,32050,32055,32061,32066,32072,32077,32083,32088,32093,32098,32104,32109, 188 32114,32119,32124,32129,32134,32139,32144,32149,32154,32158,32163,32168,32173, 189 32177,32182,32186,32191,32195,32200,32204,32209,32213,32217,32222,32226,32230, 190 32234,32238,32242,32247,32251,32255,32259,32263,32267,32270,32274,32278,32282, 191 32286,32290,32293,32297,32301,32304,32308,32311,32315,32318,32322,32325,32329, 192 32332,32336,32339,32342,32346,32349,32352,32356,32359,32362,32365,32368,32371, 193 32374,32377,32381,32384,32387,32389,32392,32395,32398,32401,32404,32407,32410, 194 32412,32415,32418,32421,32423,32426,32429,32431,32434,32437,32439,32442,32444, 195 32447,32449,32452,32454,32457,32459,32461,32464,32466,32469,32471,32473,32476, 196 32478,32480,32482,32485,32487,32489,32491,32493,32495,32497,32500,32502,32504, 197 32506,32508,32510,32512,32514,32516,32518,32520,32522,32524,32526,32527,32529, 198 32531,32533,32535,32537,32538,32540,32542,32544,32545,32547}; 199 200static uma_zone_t qdiffsample_zone; 201 202static MALLOC_DEFINE(M_CDG, "cdg data", 203 "Per connection data required for the CDG congestion control algorithm"); 204 205static int ertt_id; 206 207static VNET_DEFINE(uint32_t, cdg_alpha_inc); 208static VNET_DEFINE(uint32_t, cdg_beta_delay); 209static VNET_DEFINE(uint32_t, cdg_beta_loss); 210static VNET_DEFINE(uint32_t, cdg_smoothing_factor); 211static VNET_DEFINE(uint32_t, cdg_exp_backoff_scale); 212static VNET_DEFINE(uint32_t, cdg_consec_cong); 213static VNET_DEFINE(uint32_t, cdg_hold_backoff); 214#define V_cdg_alpha_inc VNET(cdg_alpha_inc) 215#define V_cdg_beta_delay VNET(cdg_beta_delay) 216#define V_cdg_beta_loss VNET(cdg_beta_loss) 217#define V_cdg_smoothing_factor VNET(cdg_smoothing_factor) 218#define V_cdg_exp_backoff_scale VNET(cdg_exp_backoff_scale) 219#define V_cdg_consec_cong VNET(cdg_consec_cong) 220#define V_cdg_hold_backoff VNET(cdg_hold_backoff) 221 222/* Function prototypes. */ 223static int cdg_mod_init(void); 224static int cdg_mod_destroy(void); 225static void cdg_conn_init(struct cc_var *ccv); 226static int cdg_cb_init(struct cc_var *ccv); 227static void cdg_cb_destroy(struct cc_var *ccv); 228static void cdg_cong_signal(struct cc_var *ccv, uint32_t signal_type); 229static void cdg_ack_received(struct cc_var *ccv, uint16_t ack_type); 230 231struct cc_algo cdg_cc_algo = { 232 .name = "cdg", 233 .mod_init = cdg_mod_init, 234 .ack_received = cdg_ack_received, 235 .cb_destroy = cdg_cb_destroy, 236 .cb_init = cdg_cb_init, 237 .conn_init = cdg_conn_init, 238 .cong_signal = cdg_cong_signal, 239 .mod_destroy = cdg_mod_destroy 240}; 241 242/* Vnet created and being initialised. */ 243static void 244cdg_init_vnet(const void *unused __unused) 245{ 246 247 V_cdg_alpha_inc = 0; 248 V_cdg_beta_delay = 70; 249 V_cdg_beta_loss = 50; 250 V_cdg_smoothing_factor = 8; 251 V_cdg_exp_backoff_scale = 3; 252 V_cdg_consec_cong = 5; 253 V_cdg_hold_backoff = 5; 254} 255 256static int 257cdg_mod_init(void) 258{ 259 VNET_ITERATOR_DECL(v); 260 261 ertt_id = khelp_get_id("ertt"); 262 if (ertt_id <= 0) 263 return (EINVAL); 264 265 qdiffsample_zone = uma_zcreate("cdg_qdiffsample", 266 sizeof(struct qdiff_sample), NULL, NULL, NULL, NULL, 0, 0); 267 268 VNET_LIST_RLOCK(); 269 VNET_FOREACH(v) { 270 CURVNET_SET(v); 271 cdg_init_vnet(NULL); 272 CURVNET_RESTORE(); 273 } 274 VNET_LIST_RUNLOCK(); 275 276 cdg_cc_algo.post_recovery = newreno_cc_algo.post_recovery; 277 cdg_cc_algo.after_idle = newreno_cc_algo.after_idle; 278 279 return (0); 280} 281 282static int 283cdg_mod_destroy(void) 284{ 285 286 uma_zdestroy(qdiffsample_zone); 287 return (0); 288} 289 290static int 291cdg_cb_init(struct cc_var *ccv) 292{ 293 struct cdg *cdg_data; 294 295 cdg_data = malloc(sizeof(struct cdg), M_CDG, M_NOWAIT); 296 if (cdg_data == NULL) 297 return (ENOMEM); 298 299 cdg_data->shadow_w = 0; 300 cdg_data->max_qtrend = 0; 301 cdg_data->min_qtrend = 0; 302 cdg_data->queue_state = CDG_Q_UNKNOWN; 303 cdg_data->maxrtt_in_rtt = 0; 304 cdg_data->maxrtt_in_prevrtt = 0; 305 cdg_data->minrtt_in_rtt = INT_MAX; 306 cdg_data->minrtt_in_prevrtt = 0; 307 cdg_data->window_incr = 0; 308 cdg_data->rtt_count = 0; 309 cdg_data->consec_cong_cnt = 0; 310 cdg_data->sample_q_size = V_cdg_smoothing_factor; 311 cdg_data->num_samples = 0; 312 STAILQ_INIT(&cdg_data->qdiffmin_q); 313 STAILQ_INIT(&cdg_data->qdiffmax_q); 314 315 ccv->cc_data = cdg_data; 316 317 return (0); 318} 319 320static void 321cdg_conn_init(struct cc_var *ccv) 322{ 323 struct cdg *cdg_data = ccv->cc_data; 324 325 /* 326 * Initialise the shadow_cwnd in case we are competing with loss based 327 * flows from the start 328 */ 329 cdg_data->shadow_w = CCV(ccv, snd_cwnd); 330} 331 332static void 333cdg_cb_destroy(struct cc_var *ccv) 334{ 335 struct cdg *cdg_data; 336 struct qdiff_sample *qds, *qds_n; 337 338 cdg_data = ccv->cc_data; 339 340 qds = STAILQ_FIRST(&cdg_data->qdiffmin_q); 341 while (qds != NULL) { 342 qds_n = STAILQ_NEXT(qds, qdiff_lnk); 343 uma_zfree(qdiffsample_zone,qds); 344 qds = qds_n; 345 } 346 347 qds = STAILQ_FIRST(&cdg_data->qdiffmax_q); 348 while (qds != NULL) { 349 qds_n = STAILQ_NEXT(qds, qdiff_lnk); 350 uma_zfree(qdiffsample_zone,qds); 351 qds = qds_n; 352 } 353 354 free(ccv->cc_data, M_CDG); 355} 356 357static int 358cdg_beta_handler(SYSCTL_HANDLER_ARGS) 359{ 360 361 if (req->newptr != NULL && 362 (CAST_PTR_INT(req->newptr) == 0 || CAST_PTR_INT(req->newptr) > 100)) 363 return (EINVAL); 364 365 return (sysctl_handle_int(oidp, arg1, arg2, req)); 366} 367 368static int 369cdg_exp_backoff_scale_handler(SYSCTL_HANDLER_ARGS) 370{ 371 372 if (req->newptr != NULL && CAST_PTR_INT(req->newptr) < 1) 373 return (EINVAL); 374 375 return (sysctl_handle_int(oidp, arg1, arg2, req)); 376} 377 378static inline unsigned long 379cdg_window_decrease(struct cc_var *ccv, unsigned long owin, unsigned int beta) 380{ 381 382 return ((ulmin(CCV(ccv, snd_wnd), owin) * beta) / 100); 383} 384 385/* 386 * Window increase function 387 * This window increase function is independent of the initial window size 388 * to ensure small window flows are not discriminated against (i.e. fairness). 389 * It increases at 1pkt/rtt like Reno for alpha_inc rtts, and then 2pkts/rtt for 390 * the next alpha_inc rtts, etc. 391 */ 392static void 393cdg_window_increase(struct cc_var *ccv, int new_measurement) 394{ 395 struct cdg *cdg_data; 396 int incr, s_w_incr; 397 398 cdg_data = ccv->cc_data; 399 incr = s_w_incr = 0; 400 401 if (CCV(ccv, snd_cwnd) <= CCV(ccv, snd_ssthresh)) { 402 /* Slow start. */ 403 incr = CCV(ccv, t_maxseg); 404 s_w_incr = incr; 405 cdg_data->window_incr = cdg_data->rtt_count = 0; 406 } else { 407 /* Congestion avoidance. */ 408 if (new_measurement) { 409 s_w_incr = CCV(ccv, t_maxseg); 410 if (V_cdg_alpha_inc == 0) { 411 incr = CCV(ccv, t_maxseg); 412 } else { 413 if (++cdg_data->rtt_count >= V_cdg_alpha_inc) { 414 cdg_data->window_incr++; 415 cdg_data->rtt_count = 0; 416 } 417 incr = CCV(ccv, t_maxseg) * 418 cdg_data->window_incr; 419 } 420 } 421 } 422 423 if (cdg_data->shadow_w > 0) 424 cdg_data->shadow_w = ulmin(cdg_data->shadow_w + s_w_incr, 425 TCP_MAXWIN << CCV(ccv, snd_scale)); 426 427 CCV(ccv, snd_cwnd) = ulmin(CCV(ccv, snd_cwnd) + incr, 428 TCP_MAXWIN << CCV(ccv, snd_scale)); 429} 430 431static void 432cdg_cong_signal(struct cc_var *ccv, uint32_t signal_type) 433{ 434 struct cdg *cdg_data = ccv->cc_data; 435 436 switch(signal_type) { 437 case CC_CDG_DELAY: 438 CCV(ccv, snd_ssthresh) = cdg_window_decrease(ccv, 439 CCV(ccv, snd_cwnd), V_cdg_beta_delay); 440 CCV(ccv, snd_cwnd) = CCV(ccv, snd_ssthresh); 441 CCV(ccv, snd_recover) = CCV(ccv, snd_max); 442 cdg_data->window_incr = cdg_data->rtt_count = 0; 443 ENTER_CONGRECOVERY(CCV(ccv, t_flags)); 444 break; 445 case CC_NDUPACK: 446 /* 447 * If already responding to congestion OR we have guessed no 448 * queue in the path is full. 449 */ 450 if (IN_CONGRECOVERY(CCV(ccv, t_flags)) || 451 cdg_data->queue_state < CDG_Q_FULL) { 452 CCV(ccv, snd_ssthresh) = CCV(ccv, snd_cwnd); 453 CCV(ccv, snd_recover) = CCV(ccv, snd_max); 454 } else { 455 /* 456 * Loss is likely to be congestion related. We have 457 * inferred a queue full state, so have shadow window 458 * react to loss as NewReno would. 459 */ 460 if (cdg_data->shadow_w > 0) 461 cdg_data->shadow_w = cdg_window_decrease(ccv, 462 cdg_data->shadow_w, RENO_BETA); 463 464 CCV(ccv, snd_ssthresh) = ulmax(cdg_data->shadow_w, 465 cdg_window_decrease(ccv, CCV(ccv, snd_cwnd), 466 V_cdg_beta_loss)); 467 468 cdg_data->window_incr = cdg_data->rtt_count = 0; 469 } 470 ENTER_RECOVERY(CCV(ccv, t_flags)); 471 break; 472 default: 473 newreno_cc_algo.cong_signal(ccv, signal_type); 474 break; 475 } 476} 477 478/* 479 * Using a negative exponential probabilistic backoff so that sources with 480 * varying RTTs which share the same link will, on average, have the same 481 * probability of backoff over time. 482 * 483 * Prob_backoff = 1 - exp(-qtrend / V_cdg_exp_backoff_scale), where 484 * V_cdg_exp_backoff_scale is the average qtrend for the exponential backoff. 485 */ 486static inline int 487prob_backoff(long qtrend) 488{ 489 int backoff, idx, p; 490 491 backoff = (qtrend > ((MAXGRAD * V_cdg_exp_backoff_scale) << D_P_E)); 492 493 if (!backoff) { 494 if (V_cdg_exp_backoff_scale > 1) 495 idx = (qtrend + V_cdg_exp_backoff_scale / 2) / 496 V_cdg_exp_backoff_scale; 497 else 498 idx = qtrend; 499 500 /* Backoff probability proportional to rate of queue growth. */ 501 p = (INT_MAX / (1 << EXP_PREC)) * probexp[idx]; 502 backoff = (random() < p); 503 } 504 505 return (backoff); 506} 507 508static inline void 509calc_moving_average(struct cdg *cdg_data, long qdiff_max, long qdiff_min) 510{ 511 struct qdiff_sample *qds; 512 513 ++cdg_data->num_samples; 514 if (cdg_data->num_samples > cdg_data->sample_q_size) { 515 /* Minimum RTT. */ 516 qds = STAILQ_FIRST(&cdg_data->qdiffmin_q); 517 cdg_data->min_qtrend = cdg_data->min_qtrend + 518 (qdiff_min - qds->qdiff) / cdg_data->sample_q_size; 519 STAILQ_REMOVE_HEAD(&cdg_data->qdiffmin_q, qdiff_lnk); 520 qds->qdiff = qdiff_min; 521 STAILQ_INSERT_TAIL(&cdg_data->qdiffmin_q, qds, qdiff_lnk); 522 523 /* Maximum RTT. */ 524 qds = STAILQ_FIRST(&cdg_data->qdiffmax_q); 525 cdg_data->max_qtrend = cdg_data->max_qtrend + 526 (qdiff_max - qds->qdiff) / cdg_data->sample_q_size; 527 STAILQ_REMOVE_HEAD(&cdg_data->qdiffmax_q, qdiff_lnk); 528 qds->qdiff = qdiff_max; 529 STAILQ_INSERT_TAIL(&cdg_data->qdiffmax_q, qds, qdiff_lnk); 530 --cdg_data->num_samples; 531 } else { 532 qds = uma_zalloc(qdiffsample_zone, M_NOWAIT); 533 if (qds != NULL) { 534 cdg_data->min_qtrend = cdg_data->min_qtrend + 535 qdiff_min / cdg_data->sample_q_size; 536 qds->qdiff = qdiff_min; 537 STAILQ_INSERT_TAIL(&cdg_data->qdiffmin_q, qds, 538 qdiff_lnk); 539 } 540 541 qds = uma_zalloc(qdiffsample_zone, M_NOWAIT); 542 if (qds) { 543 cdg_data->max_qtrend = cdg_data->max_qtrend + 544 qdiff_max / cdg_data->sample_q_size; 545 qds->qdiff = qdiff_max; 546 STAILQ_INSERT_TAIL(&cdg_data->qdiffmax_q, qds, 547 qdiff_lnk); 548 } 549 } 550} 551 552static void 553cdg_ack_received(struct cc_var *ccv, uint16_t ack_type) 554{ 555 struct cdg *cdg_data; 556 struct ertt *e_t; 557 long qdiff_max, qdiff_min; 558 int congestion, new_measurement, slowstart; 559 560 cdg_data = ccv->cc_data; 561 e_t = (struct ertt *)khelp_get_osd(CCV(ccv, osd), ertt_id); 562 new_measurement = e_t->flags & ERTT_NEW_MEASUREMENT; 563 congestion = 0; 564 cdg_data->maxrtt_in_rtt = imax(e_t->rtt, cdg_data->maxrtt_in_rtt); 565 cdg_data->minrtt_in_rtt = imin(e_t->rtt, cdg_data->minrtt_in_rtt); 566 567 if (new_measurement) { 568 slowstart = (CCV(ccv, snd_cwnd) <= CCV(ccv, snd_ssthresh)); 569 /* 570 * Update smoothed gradient measurements. Since we are only 571 * using one measurement per RTT, use max or min rtt_in_rtt. 572 * This is also less noisy than a sample RTT measurement. Max 573 * RTT measurements can have trouble due to OS issues. 574 */ 575 if (cdg_data->maxrtt_in_prevrtt) { 576 qdiff_max = ((long)(cdg_data->maxrtt_in_rtt - 577 cdg_data->maxrtt_in_prevrtt) << D_P_E ); 578 qdiff_min = ((long)(cdg_data->minrtt_in_rtt - 579 cdg_data->minrtt_in_prevrtt) << D_P_E ); 580 581 calc_moving_average(cdg_data, qdiff_max, qdiff_min); 582 583 /* Probabilistic backoff with respect to gradient. */ 584 if (slowstart && qdiff_min > 0) 585 congestion = prob_backoff(qdiff_min); 586 else if (cdg_data->min_qtrend > 0) 587 congestion = prob_backoff(cdg_data->min_qtrend); 588 else if (slowstart && qdiff_max > 0) 589 congestion = prob_backoff(qdiff_max); 590 else if (cdg_data->max_qtrend > 0) 591 congestion = prob_backoff(cdg_data->max_qtrend); 592 593 /* Update estimate of queue state. */ 594 if (cdg_data->min_qtrend > 0 && 595 cdg_data->max_qtrend <= 0) { 596 cdg_data->queue_state = CDG_Q_FULL; 597 } else if (cdg_data->min_qtrend >= 0 && 598 cdg_data->max_qtrend < 0) { 599 cdg_data->queue_state = CDG_Q_EMPTY; 600 cdg_data->shadow_w = 0; 601 } else if (cdg_data->min_qtrend > 0 && 602 cdg_data->max_qtrend > 0) { 603 cdg_data->queue_state = CDG_Q_RISING; 604 } else if (cdg_data->min_qtrend < 0 && 605 cdg_data->max_qtrend < 0) { 606 cdg_data->queue_state = CDG_Q_FALLING; 607 } 608 609 if (cdg_data->min_qtrend < 0 || 610 cdg_data->max_qtrend < 0) 611 cdg_data->consec_cong_cnt = 0; 612 } 613 614 cdg_data->minrtt_in_prevrtt = cdg_data->minrtt_in_rtt; 615 cdg_data->minrtt_in_rtt = INT_MAX; 616 cdg_data->maxrtt_in_prevrtt = cdg_data->maxrtt_in_rtt; 617 cdg_data->maxrtt_in_rtt = 0; 618 e_t->flags &= ~ERTT_NEW_MEASUREMENT; 619 } 620 621 if (congestion) { 622 cdg_data->consec_cong_cnt++; 623 if (!IN_RECOVERY(CCV(ccv, t_flags))) { 624 if (cdg_data->consec_cong_cnt <= V_cdg_consec_cong) 625 cdg_cong_signal(ccv, CC_CDG_DELAY); 626 else 627 /* 628 * We have been backing off but the queue is not 629 * falling. Assume we are competing with 630 * loss-based flows and don't back off for the 631 * next V_cdg_hold_backoff RTT periods. 632 */ 633 if (cdg_data->consec_cong_cnt >= 634 V_cdg_consec_cong + V_cdg_hold_backoff) 635 cdg_data->consec_cong_cnt = 0; 636 637 /* Won't see effect until 2nd RTT. */ 638 cdg_data->maxrtt_in_prevrtt = 0; 639 /* 640 * Resync shadow window in case we are competing with a 641 * loss based flow 642 */ 643 cdg_data->shadow_w = ulmax(CCV(ccv, snd_cwnd), 644 cdg_data->shadow_w); 645 } 646 } else if (ack_type == CC_ACK) 647 cdg_window_increase(ccv, new_measurement); 648} 649 650/* When a vnet is created and being initialised, init the per-stack CDG vars. */ 651VNET_SYSINIT(cdg_init_vnet, SI_SUB_PROTO_BEGIN, SI_ORDER_FIRST, 652 cdg_init_vnet, NULL); 653 654SYSCTL_DECL(_net_inet_tcp_cc_cdg); 655SYSCTL_NODE(_net_inet_tcp_cc, OID_AUTO, cdg, CTLFLAG_RW, NULL, 656 "CAIA delay-gradient congestion control related settings"); 657 658SYSCTL_STRING(_net_inet_tcp_cc_cdg, OID_AUTO, version, 659 CTLFLAG_RD, CDG_VERSION, sizeof(CDG_VERSION) - 1, 660 "Current algorithm/implementation version number"); 661 662SYSCTL_VNET_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, alpha_inc, 663 CTLFLAG_RW, &VNET_NAME(cdg_alpha_inc), 0, 664 "Increment the window increase factor alpha by 1 MSS segment every " 665 "alpha_inc RTTs during congestion avoidance mode."); 666 667SYSCTL_VNET_PROC(_net_inet_tcp_cc_cdg, OID_AUTO, beta_delay, 668 CTLTYPE_UINT|CTLFLAG_RW, &VNET_NAME(cdg_beta_delay), 70, 669 &cdg_beta_handler, "IU", 670 "Delay-based window decrease factor as a percentage " 671 "(on delay-based backoff, w = w * beta_delay / 100)"); 672 673SYSCTL_VNET_PROC(_net_inet_tcp_cc_cdg, OID_AUTO, beta_loss, 674 CTLTYPE_UINT|CTLFLAG_RW, &VNET_NAME(cdg_beta_loss), 50, 675 &cdg_beta_handler, "IU", 676 "Loss-based window decrease factor as a percentage " 677 "(on loss-based backoff, w = w * beta_loss / 100)"); 678 679SYSCTL_VNET_PROC(_net_inet_tcp_cc_cdg, OID_AUTO, exp_backoff_scale, 680 CTLTYPE_UINT|CTLFLAG_RW, &VNET_NAME(cdg_exp_backoff_scale), 2, 681 &cdg_exp_backoff_scale_handler, "IU", 682 "Scaling parameter for the probabilistic exponential backoff"); 683 684SYSCTL_VNET_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, smoothing_factor, 685 CTLFLAG_RW, &VNET_NAME(cdg_smoothing_factor), 8, 686 "Number of samples used for moving average smoothing (0 = no smoothing)"); 687 688SYSCTL_VNET_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, loss_compete_consec_cong, 689 CTLFLAG_RW, &VNET_NAME(cdg_consec_cong), 5, 690 "Number of consecutive delay-gradient based congestion episodes which will " 691 "trigger loss based CC compatibility"); 692 693SYSCTL_VNET_UINT(_net_inet_tcp_cc_cdg, OID_AUTO, loss_compete_hold_backoff, 694 CTLFLAG_RW, &VNET_NAME(cdg_hold_backoff), 5, 695 "Number of consecutive delay-gradient based congestion episodes to hold " 696 "the window backoff for loss based CC compatibility"); 697 698DECLARE_CC_MODULE(cdg, &cdg_cc_algo); 699 700MODULE_DEPEND(cdg, ertt, 1, 1, 1); 701