mirror of
https://gitlab.com/chrony/chrony.git
synced 2025-12-03 15:45:07 -05:00
Add a new parameter to limit the negative value of the step state variable. It's set as a maximum delay in number of updates before the actual step applied to the quantile estimate starts growing from the minimum step when the input value is consistently larger or smaller than the estimate. This prevents the algorithm from effectively becoming the slower 1U variant if the quantile estimate is stable most of the time. Set it to 100 updates for the NTP delay and 1000 updates for the hwclock delay. An option could be added later to make it configurable.
236 lines
6.0 KiB
C
236 lines
6.0 KiB
C
/*
|
|
chronyd/chronyc - Programs for keeping computer clocks accurate.
|
|
|
|
**********************************************************************
|
|
* Copyright (C) Miroslav Lichvar 2022
|
|
*
|
|
* This program is free software; you can redistribute it and/or modify
|
|
* it under the terms of version 2 of the GNU General Public License as
|
|
* published by the Free Software Foundation.
|
|
*
|
|
* This program is distributed in the hope that it will be useful, but
|
|
* WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
* General Public License for more details.
|
|
*
|
|
* You should have received a copy of the GNU General Public License along
|
|
* with this program; if not, write to the Free Software Foundation, Inc.,
|
|
* 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
|
|
*
|
|
**********************************************************************
|
|
|
|
=======================================================================
|
|
|
|
Estimation of quantiles using the Frugal-2U streaming algorithm
|
|
(https://arxiv.org/pdf/1407.1121v1.pdf)
|
|
*/
|
|
|
|
#include "config.h"
|
|
|
|
#include "logging.h"
|
|
#include "memory.h"
|
|
#include "quantiles.h"
|
|
#include "regress.h"
|
|
#include "util.h"
|
|
|
|
/* Maximum number of repeated estimates for stabilisation */
|
|
#define MAX_REPEAT 64
|
|
|
|
struct Quantile {
|
|
double est;
|
|
double step;
|
|
int sign;
|
|
};
|
|
|
|
struct QNT_Instance_Record {
|
|
struct Quantile *quants;
|
|
int n_quants;
|
|
int repeat;
|
|
int q;
|
|
int min_k;
|
|
double min_step;
|
|
double neg_step_limit;
|
|
int n_set;
|
|
};
|
|
|
|
/* ================================================== */
|
|
|
|
QNT_Instance
|
|
QNT_CreateInstance(int min_k, int max_k, int q, int repeat,
|
|
int large_step_delay, double min_step)
|
|
{
|
|
QNT_Instance inst;
|
|
long seed;
|
|
|
|
if (q < 2 || min_k > max_k || min_k < 1 || max_k >= q ||
|
|
repeat < 1 || repeat > MAX_REPEAT || min_step <= 0.0 || large_step_delay < 0)
|
|
assert(0);
|
|
|
|
inst = MallocNew(struct QNT_Instance_Record);
|
|
inst->n_quants = (max_k - min_k + 1) * repeat;
|
|
inst->quants = MallocArray(struct Quantile, inst->n_quants);
|
|
inst->repeat = repeat;
|
|
inst->q = q;
|
|
inst->min_k = min_k;
|
|
inst->min_step = min_step;
|
|
inst->neg_step_limit = -large_step_delay * min_step;
|
|
|
|
QNT_Reset(inst);
|
|
|
|
/* Seed the random number generator, which will not be isolated from
|
|
other instances and other random() users */
|
|
UTI_GetRandomBytes(&seed, sizeof (seed));
|
|
srandom(seed);
|
|
|
|
return inst;
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
void
|
|
QNT_DestroyInstance(QNT_Instance inst)
|
|
{
|
|
Free(inst->quants);
|
|
Free(inst);
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
void
|
|
QNT_Reset(QNT_Instance inst)
|
|
{
|
|
int i;
|
|
|
|
inst->n_set = 0;
|
|
|
|
for (i = 0; i < inst->n_quants; i++) {
|
|
inst->quants[i].est = 0.0;
|
|
inst->quants[i].step = inst->min_step;
|
|
inst->quants[i].sign = 1;
|
|
}
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
static void
|
|
insert_initial_value(QNT_Instance inst, double value)
|
|
{
|
|
int i, j, r = inst->repeat;
|
|
|
|
if (inst->n_set * r >= inst->n_quants)
|
|
assert(0);
|
|
|
|
/* Keep the initial estimates repeated and ordered */
|
|
for (i = inst->n_set; i > 0 && inst->quants[(i - 1) * r].est > value; i--) {
|
|
for (j = 0; j < r; j++)
|
|
inst->quants[i * r + j].est = inst->quants[(i - 1) * r].est;
|
|
}
|
|
|
|
for (j = 0; j < r; j++)
|
|
inst->quants[i * r + j].est = value;
|
|
inst->n_set++;
|
|
|
|
/* Duplicate the largest value in unset quantiles */
|
|
for (i = inst->n_set * r; i < inst->n_quants; i++)
|
|
inst->quants[i].est = inst->quants[i - 1].est;
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
static void
|
|
update_estimate(struct Quantile *quantile, double value, double p, double rand,
|
|
double min_step, double neg_step_limit)
|
|
{
|
|
if (value >= quantile->est) {
|
|
if (rand < (1.0 - p))
|
|
return;
|
|
quantile->step += quantile->sign > 0 ? min_step : -min_step;
|
|
quantile->est += quantile->step > min_step ? quantile->step : min_step;
|
|
if (quantile->est > value) {
|
|
quantile->step += value - quantile->est;
|
|
quantile->est = value + min_step / 4.0;
|
|
}
|
|
if (quantile->sign < 0 && quantile->step > min_step)
|
|
quantile->step = min_step;
|
|
quantile->sign = 1;
|
|
} else {
|
|
if (rand < p)
|
|
return;
|
|
quantile->step += quantile->sign < 0 ? min_step : -min_step;
|
|
quantile->est -= quantile->step > min_step ? quantile->step : min_step;
|
|
if (quantile->est < value) {
|
|
quantile->step += quantile->est - value;
|
|
quantile->est = value - min_step / 4.0;
|
|
}
|
|
if (quantile->sign > 0 && quantile->step > min_step)
|
|
quantile->step = min_step;
|
|
quantile->sign = -1;
|
|
}
|
|
|
|
if (quantile->step < neg_step_limit)
|
|
quantile->step = neg_step_limit;
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
void
|
|
QNT_Accumulate(QNT_Instance inst, double value)
|
|
{
|
|
double p, rand;
|
|
int i;
|
|
|
|
/* Initialise the estimates with first received values */
|
|
if (inst->n_set * inst->repeat < inst->n_quants) {
|
|
insert_initial_value(inst, value);
|
|
return;
|
|
}
|
|
|
|
for (i = 0; i < inst->n_quants; i++) {
|
|
p = (double)(i / inst->repeat + inst->min_k) / inst->q;
|
|
rand = (double)random() / ((1U << 31) - 1);
|
|
|
|
update_estimate(&inst->quants[i], value, p, rand, inst->min_step, inst->neg_step_limit);
|
|
}
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
int
|
|
QNT_GetMinK(QNT_Instance inst)
|
|
{
|
|
return inst->min_k;
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
int
|
|
QNT_GetMaxK(QNT_Instance inst)
|
|
{
|
|
return inst->min_k + (inst->n_quants / inst->repeat) - 1;
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
double
|
|
QNT_GetMinStep(QNT_Instance inst)
|
|
{
|
|
return inst->min_step;
|
|
}
|
|
|
|
/* ================================================== */
|
|
|
|
double
|
|
QNT_GetQuantile(QNT_Instance inst, int k)
|
|
{
|
|
double estimates[MAX_REPEAT];
|
|
int i;
|
|
|
|
if (k < inst->min_k || (k - inst->min_k) * inst->repeat >= inst->n_quants)
|
|
assert(0);
|
|
|
|
for (i = 0; i < inst->repeat; i++)
|
|
estimates[i] = inst->quants[(k - inst->min_k) * inst->repeat + i].est;
|
|
|
|
return RGR_FindMedian(estimates, inst->repeat);
|
|
}
|