Release 4.15 include/net/red.h
/* SPDX-License-Identifier: GPL-2.0 */
#ifndef __NET_SCHED_RED_H
#define __NET_SCHED_RED_H
#include <linux/types.h>
#include <linux/bug.h>
#include <net/pkt_sched.h>
#include <net/inet_ecn.h>
#include <net/dsfield.h>
#include <linux/reciprocal_div.h>
/* Random Early Detection (RED) algorithm.
=======================================
Source: Sally Floyd and Van Jacobson, "Random Early Detection Gateways
for Congestion Avoidance", 1993, IEEE/ACM Transactions on Networking.
This file codes a "divisionless" version of RED algorithm
as written down in Fig.17 of the paper.
Short description.
------------------
When a new packet arrives we calculate the average queue length:
avg = (1-W)*avg + W*current_queue_len,
W is the filter time constant (chosen as 2^(-Wlog)), it controls
the inertia of the algorithm. To allow larger bursts, W should be
decreased.
if (avg > th_max) -> packet marked (dropped).
if (avg < th_min) -> packet passes.
if (th_min < avg < th_max) we calculate probability:
Pb = max_P * (avg - th_min)/(th_max-th_min)
and mark (drop) packet with this probability.
Pb changes from 0 (at avg==th_min) to max_P (avg==th_max).
max_P should be small (not 1), usually 0.01..0.02 is good value.
max_P is chosen as a number, so that max_P/(th_max-th_min)
is a negative power of two in order arithmetics to contain
only shifts.
Parameters, settable by user:
-----------------------------
qth_min - bytes (should be < qth_max/2)
qth_max - bytes (should be at least 2*qth_min and less limit)
Wlog - bits (<32) log(1/W).
Plog - bits (<32)
Plog is related to max_P by formula:
max_P = (qth_max-qth_min)/2^Plog;
F.e. if qth_max=128K and qth_min=32K, then Plog=22
corresponds to max_P=0.02
Scell_log
Stab
Lookup table for log((1-W)^(t/t_ave).
NOTES:
Upper bound on W.
-----------------
If you want to allow bursts of L packets of size S,
you should choose W:
L + 1 - th_min/S < (1-(1-W)^L)/W
th_min/S = 32 th_min/S = 4
log(W) L
-1 33
-2 35
-3 39
-4 46
-5 57
-6 75
-7 101
-8 135
-9 190
etc.
*/
/*
* Adaptative RED : An Algorithm for Increasing the Robustness of RED's AQM
* (Sally FLoyd, Ramakrishna Gummadi, and Scott Shenker) August 2001
*
* Every 500 ms:
* if (avg > target and max_p <= 0.5)
* increase max_p : max_p += alpha;
* else if (avg < target and max_p >= 0.01)
* decrease max_p : max_p *= beta;
*
* target :[qth_min + 0.4*(qth_min - qth_max),
* qth_min + 0.6*(qth_min - qth_max)].
* alpha : min(0.01, max_p / 4)
* beta : 0.9
* max_P is a Q0.32 fixed point number (with 32 bits mantissa)
* max_P between 0.01 and 0.5 (1% - 50%) [ Its no longer a negative power of two ]
*/
#define RED_ONE_PERCENT ((u32)DIV_ROUND_CLOSEST(1ULL<<32, 100))
#define MAX_P_MIN (1 * RED_ONE_PERCENT)
#define MAX_P_MAX (50 * RED_ONE_PERCENT)
#define MAX_P_ALPHA(val) min(MAX_P_MIN, val / 4)
#define RED_STAB_SIZE 256
#define RED_STAB_MASK (RED_STAB_SIZE - 1)
struct red_stats {
u32 prob_drop; /* Early probability drops */
u32 prob_mark; /* Early probability marks */
u32 forced_drop; /* Forced drops, qavg > max_thresh */
u32 forced_mark; /* Forced marks, qavg > max_thresh */
u32 pdrop; /* Drops due to queue limits */
u32 other; /* Drops due to drop() calls */
};
struct red_parms {
/* Parameters */
u32 qth_min; /* Min avg length threshold: Wlog scaled */
u32 qth_max; /* Max avg length threshold: Wlog scaled */
u32 Scell_max;
u32 max_P; /* probability, [0 .. 1.0] 32 scaled */
/* reciprocal_value(max_P / qth_delta) */
struct reciprocal_value max_P_reciprocal;
u32 qth_delta; /* max_th - min_th */
u32 target_min; /* min_th + 0.4*(max_th - min_th) */
u32 target_max; /* min_th + 0.6*(max_th - min_th) */
u8 Scell_log;
u8 Wlog; /* log(W) */
u8 Plog; /* random number bits */
u8 Stab[RED_STAB_SIZE];
};
struct red_vars {
/* Variables */
int qcount; /* Number of packets since last random
number generation */
u32 qR; /* Cached random number */
unsigned long qavg; /* Average queue length: Wlog scaled */
ktime_t qidlestart; /* Start of current idle period */
};
static inline u32 red_maxp(u8 Plog)
{
return Plog < 32 ? (~0U >> Plog) : ~0U;
}
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| Total | 25 | 100.00% | 2 | 100.00% |
static inline void red_set_vars(struct red_vars *v)
{
/* Reset average queue length, the value is strictly bound
* to the parameters below, reseting hurts a bit but leaving
* it might result in an unreasonable qavg for a while. --TGR
*/
v->qavg = 0;
v->qcount = -1;
}
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static inline bool red_check_params(u32 qth_min, u32 qth_max, u8 Wlog)
{
if (fls(qth_min) + Wlog > 32)
return false;
if (fls(qth_max) + Wlog > 32)
return false;
if (qth_max < qth_min)
return false;
return true;
}
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static inline void red_set_parms(struct red_parms *p,
u32 qth_min, u32 qth_max, u8 Wlog, u8 Plog,
u8 Scell_log, u8 *stab, u32 max_P)
{
int delta = qth_max - qth_min;
u32 max_p_delta;
p->qth_min = qth_min << Wlog;
p->qth_max = qth_max << Wlog;
p->Wlog = Wlog;
p->Plog = Plog;
if (delta <= 0)
delta = 1;
p->qth_delta = delta;
if (!max_P) {
max_P = red_maxp(Plog);
max_P *= delta; /* max_P = (qth_max - qth_min)/2^Plog */
}
p->max_P = max_P;
max_p_delta = max_P / delta;
max_p_delta = max(max_p_delta, 1U);
p->max_P_reciprocal = reciprocal_value(max_p_delta);
/* RED Adaptative target :
* [min_th + 0.4*(min_th - max_th),
* min_th + 0.6*(min_th - max_th)].
*/
delta /= 5;
p->target_min = qth_min + 2*delta;
p->target_max = qth_min + 3*delta;
p->Scell_log = Scell_log;
p->Scell_max = (255 << Scell_log);
if (stab)
memcpy(p->Stab, stab, sizeof(p->Stab));
}
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| Eric Dumazet | 99 | 50.00% | 3 | 60.00% |
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| Nogah Frankel | 1 | 0.51% | 1 | 20.00% |
| Total | 198 | 100.00% | 5 | 100.00% |
static inline int red_is_idling(const struct red_vars *v)
{
return v->qidlestart != 0;
}
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| Thomas Graf | 14 | 70.00% | 1 | 20.00% |
| Eric Dumazet | 5 | 25.00% | 3 | 60.00% |
| Patrick McHardy | 1 | 5.00% | 1 | 20.00% |
| Total | 20 | 100.00% | 5 | 100.00% |
static inline void red_start_of_idle_period(struct red_vars *v)
{
v->qidlestart = ktime_get();
}
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| Thomas Graf | 13 | 68.42% | 1 | 25.00% |
| Eric Dumazet | 4 | 21.05% | 2 | 50.00% |
| Patrick McHardy | 2 | 10.53% | 1 | 25.00% |
| Total | 19 | 100.00% | 4 | 100.00% |
static inline void red_end_of_idle_period(struct red_vars *v)
{
v->qidlestart = 0;
}
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| Thomas Graf | 13 | 72.22% | 1 | 25.00% |
| Eric Dumazet | 4 | 22.22% | 2 | 50.00% |
| Patrick McHardy | 1 | 5.56% | 1 | 25.00% |
| Total | 18 | 100.00% | 4 | 100.00% |
static inline void red_restart(struct red_vars *v)
{
red_end_of_idle_period(v);
v->qavg = 0;
v->qcount = -1;
}
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| Person | Tokens | Prop | Commits | CommitProp |
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| Eric Dumazet | 5 | 16.67% | 1 | 50.00% |
| Total | 30 | 100.00% | 2 | 100.00% |
static inline unsigned long red_calc_qavg_from_idle_time(const struct red_parms *p,
const struct red_vars *v)
{
s64 delta = ktime_us_delta(ktime_get(), v->qidlestart);
long us_idle = min_t(s64, delta, p->Scell_max);
int shift;
/*
* The problem: ideally, average length queue recalcultion should
* be done over constant clock intervals. This is too expensive, so
* that the calculation is driven by outgoing packets.
* When the queue is idle we have to model this clock by hand.
*
* SF+VJ proposed to "generate":
*
* m = idletime / (average_pkt_size / bandwidth)
*
* dummy packets as a burst after idle time, i.e.
*
* v->qavg *= (1-W)^m
*
* This is an apparently overcomplicated solution (f.e. we have to
* precompute a table to make this calculation in reasonable time)
* I believe that a simpler model may be used here,
* but it is field for experiments.
*/
shift = p->Stab[(us_idle >> p->Scell_log) & RED_STAB_MASK];
if (shift)
return v->qavg >> shift;
else {
/* Approximate initial part of exponent with linear function:
*
* (1-W)^m ~= 1-mW + ...
*
* Seems, it is the best solution to
* problem of too coarse exponent tabulation.
*/
us_idle = (v->qavg * (u64)us_idle) >> p->Scell_log;
if (us_idle < (v->qavg >> 1))
return v->qavg - us_idle;
else
return v->qavg >> 1;
}
}
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| Ilpo Järvinen | 3 | 2.36% | 1 | 16.67% |
| David Ward | 1 | 0.79% | 1 | 16.67% |
| Total | 127 | 100.00% | 6 | 100.00% |
static inline unsigned long red_calc_qavg_no_idle_time(const struct red_parms *p,
const struct red_vars *v,
unsigned int backlog)
{
/*
* NOTE: v->qavg is fixed point number with point at Wlog.
* The formula below is equvalent to floating point
* version:
*
* qavg = qavg*(1-W) + backlog*W;
*
* --ANK (980924)
*/
return v->qavg + (backlog - (v->qavg >> p->Wlog));
}
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| Thomas Graf | 34 | 77.27% | 1 | 25.00% |
| Eric Dumazet | 9 | 20.45% | 2 | 50.00% |
| David Ward | 1 | 2.27% | 1 | 25.00% |
| Total | 44 | 100.00% | 4 | 100.00% |
static inline unsigned long red_calc_qavg(const struct red_parms *p,
const struct red_vars *v,
unsigned int backlog)
{
if (!red_is_idling(v))
return red_calc_qavg_no_idle_time(p, v, backlog);
else
return red_calc_qavg_from_idle_time(p, v);
}
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| Thomas Graf | 39 | 76.47% | 1 | 33.33% |
| Eric Dumazet | 12 | 23.53% | 2 | 66.67% |
| Total | 51 | 100.00% | 3 | 100.00% |
static inline u32 red_random(const struct red_parms *p)
{
return reciprocal_divide(prandom_u32(), p->max_P_reciprocal);
}
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| Thomas Graf | 17 | 70.83% | 1 | 33.33% |
| Eric Dumazet | 6 | 25.00% | 1 | 33.33% |
| Aruna-Hewapathirane | 1 | 4.17% | 1 | 33.33% |
| Total | 24 | 100.00% | 3 | 100.00% |
static inline int red_mark_probability(const struct red_parms *p,
const struct red_vars *v,
unsigned long qavg)
{
/* The formula used below causes questions.
OK. qR is random number in the interval
(0..1/max_P)*(qth_max-qth_min)
i.e. 0..(2^Plog). If we used floating point
arithmetics, it would be: (2^Plog)*rnd_num,
where rnd_num is less 1.
Taking into account, that qavg have fixed
point at Wlog, two lines
below have the following floating point equivalent:
max_P*(qavg - qth_min)/(qth_max-qth_min) < rnd/qcount
Any questions? --ANK (980924)
*/
return !(((qavg - p->qth_min) >> p->Wlog) * v->qcount < v->qR);
}
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| Total | 50 | 100.00% | 3 | 100.00% |
enum {
RED_BELOW_MIN_THRESH,
RED_BETWEEN_TRESH,
RED_ABOVE_MAX_TRESH,
};
static inline int red_cmp_thresh(const struct red_parms *p, unsigned long qavg)
{
if (qavg < p->qth_min)
return RED_BELOW_MIN_THRESH;
else if (qavg >= p->qth_max)
return RED_ABOVE_MAX_TRESH;
else
return RED_BETWEEN_TRESH;
}
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| Eric Dumazet | 1 | 2.27% | 1 | 50.00% |
| Total | 44 | 100.00% | 2 | 100.00% |
enum {
RED_DONT_MARK,
RED_PROB_MARK,
RED_HARD_MARK,
};
static inline int red_action(const struct red_parms *p,
struct red_vars *v,
unsigned long qavg)
{
switch (red_cmp_thresh(p, qavg)) {
case RED_BELOW_MIN_THRESH:
v->qcount = -1;
return RED_DONT_MARK;
case RED_BETWEEN_TRESH:
if (++v->qcount) {
if (red_mark_probability(p, v, qavg)) {
v->qcount = 0;
v->qR = red_random(p);
return RED_PROB_MARK;
}
} else
v->qR = red_random(p);
return RED_DONT_MARK;
case RED_ABOVE_MAX_TRESH:
v->qcount = -1;
return RED_HARD_MARK;
}
BUG();
return RED_DONT_MARK;
}
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| Thomas Graf | 107 | 88.43% | 1 | 50.00% |
| Eric Dumazet | 14 | 11.57% | 1 | 50.00% |
| Total | 121 | 100.00% | 2 | 100.00% |
static inline void red_adaptative_algo(struct red_parms *p, struct red_vars *v)
{
unsigned long qavg;
u32 max_p_delta;
qavg = v->qavg;
if (red_is_idling(v))
qavg = red_calc_qavg_from_idle_time(p, v);
/* v->qavg is fixed point number with point at Wlog */
qavg >>= p->Wlog;
if (qavg > p->target_max && p->max_P <= MAX_P_MAX)
p->max_P += MAX_P_ALPHA(p->max_P); /* maxp = maxp + alpha */
else if (qavg < p->target_min && p->max_P >= MAX_P_MIN)
p->max_P = (p->max_P/10)*9; /* maxp = maxp * Beta */
max_p_delta = DIV_ROUND_CLOSEST(p->max_P, p->qth_delta);
max_p_delta = max(max_p_delta, 1U);
p->max_P_reciprocal = reciprocal_value(max_p_delta);
}
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| Total | 140 | 100.00% | 4 | 100.00% |
#endif
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| Patrick McHardy | 4 | 0.34% | 2 | 12.50% |
| David Ward | 3 | 0.26% | 1 | 6.25% |
| Hannes Frederic Sowa | 3 | 0.26% | 1 | 6.25% |
| Paul Gortmaker | 3 | 0.26% | 1 | 6.25% |
| Ilpo Järvinen | 3 | 0.26% | 1 | 6.25% |
| Aruna-Hewapathirane | 1 | 0.09% | 1 | 6.25% |
| Greg Kroah-Hartman | 1 | 0.09% | 1 | 6.25% |
| Total | 1174 | 100.00% | 16 | 100.00% |
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