Adding upstream version 4.3.upstream/4.3upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 1040 insertions, 0 deletions

diff --git a/sourcestats.c b/sourcestats.c
new file mode 100644
index 0000000..eb4705e
--- /dev/null
+++ b/sourcestats.c
@@ -0,0 +1,1040 @@
+/*
+  chronyd/chronyc - Programs for keeping computer clocks accurate.
+
+ **********************************************************************
+ * Copyright (C) Richard P. Curnow  1997-2003
+ * Copyright (C) Miroslav Lichvar  2011-2014, 2016-2018, 2021
+ * 
+ * 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.
+ * 
+ **********************************************************************
+
+  =======================================================================
+
+  This file contains the routines that do the statistical
+  analysis on the samples obtained from the sources,
+  to determined frequencies and error bounds. */
+
+#include "config.h"
+
+#include "sysincl.h"
+
+#include "sourcestats.h"
+#include "memory.h"
+#include "regress.h"
+#include "util.h"
+#include "conf.h"
+#include "logging.h"
+#include "local.h"
+
+/* ================================================== */
+/* Define the maxumum number of samples that we want
+   to store per source */
+#define MAX_SAMPLES 64
+
+/* This is the assumed worst case bound on an unknown frequency,
+   2000ppm, which would be pretty bad */
+#define WORST_CASE_FREQ_BOUND (2000.0/1.0e6)
+
+/* The minimum and maximum assumed skew */
+#define MIN_SKEW 1.0e-12
+#define MAX_SKEW 1.0e+02
+
+/* The minimum standard deviation */
+#define MIN_STDDEV 1.0e-9
+
+/* The worst case bound on an unknown standard deviation of the offset */
+#define WORST_CASE_STDDEV_BOUND 4.0
+
+/* The asymmetry of network jitter when all jitter is in one direction */
+#define MAX_ASYMMETRY 0.5
+
+/* The minimum estimated asymmetry that can activate the offset correction */
+#define MIN_ASYMMETRY 0.45
+
+/* The minimum number of consecutive asymmetries with the same sign needed
+   to activate the offset correction */
+#define MIN_ASYMMETRY_RUN 10
+
+/* The maximum value of the counter */
+#define MAX_ASYMMETRY_RUN 1000
+
+/* ================================================== */
+
+static LOG_FileID logfileid;
+
+/* ================================================== */
+/* This data structure is used to hold the history of data from the
+   source */
+
+struct SST_Stats_Record {
+
+  /* Reference ID and IP address of source, used for logging to statistics log */
+  uint32_t refid;
+  IPAddr *ip_addr;
+
+  /* User defined minimum and maximum number of samples */
+  int min_samples;
+  int max_samples;
+
+  /* User defined minimum delay */
+  double fixed_min_delay;
+
+  /* User defined asymmetry of network jitter */
+  double fixed_asymmetry;
+
+  /* Number of samples currently stored.  The samples are stored in circular
+     buffer. */
+  int n_samples;
+
+  /* Number of extra samples stored in sample_times, offsets and peer_delays
+     arrays that are used to extend the runs test */
+  int runs_samples;
+
+  /* The index of the newest sample */
+  int last_sample;
+
+  /* Flag indicating whether last regression was successful */
+  int regression_ok;
+
+  /* The best individual sample that we are holding, in terms of the minimum
+     root distance at the present time */
+  int best_single_sample;
+
+  /* The index of the sample with minimum delay in peer_delays */
+  int min_delay_sample;
+
+  /* This is the estimated offset (+ve => local fast) at a particular time */
+  double estimated_offset;
+  double estimated_offset_sd;
+  struct timespec offset_time;
+
+  /* Number of runs of the same sign amongst the residuals */
+  int nruns;
+
+  /* Number of consecutive estimated asymmetries with the same sign.
+     The sign of the number encodes the sign of the asymmetry. */
+  int asymmetry_run;
+
+  /* This is the latest estimated asymmetry of network jitter */
+  double asymmetry;
+
+  /* This value contains the estimated frequency.  This is the number
+     of seconds that the local clock gains relative to the reference
+     source per unit local time.  (Positive => local clock fast,
+     negative => local clock slow) */
+  double estimated_frequency;
+  double estimated_frequency_sd;
+
+  /* This is the assumed worst case bounds on the estimated frequency.
+     We assume that the true frequency lies within +/- half this much
+     about estimated_frequency */
+  double skew;
+
+  /* This is the estimated standard deviation of the data points */
+  double std_dev;
+
+  /* This array contains the sample epochs, in terms of the local
+     clock. */
+  struct timespec sample_times[MAX_SAMPLES * REGRESS_RUNS_RATIO];
+
+  /* This is an array of offsets, in seconds, corresponding to the
+     sample times.  In this module, we use the convention that
+     positive means the local clock is FAST of the source and negative
+     means it is SLOW.  This is contrary to the convention in the NTP
+     stuff. */
+  double offsets[MAX_SAMPLES * REGRESS_RUNS_RATIO];
+
+  /* This is an array of the offsets as originally measured.  Local
+     clock fast of real time is indicated by positive values.  This
+     array is not slewed to adjust the readings when we apply
+     adjustments to the local clock, as is done for the array
+     'offset'. */
+  double orig_offsets[MAX_SAMPLES];
+
+  /* This is an array of peer delays, in seconds, being the roundtrip
+     measurement delay to the peer */
+  double peer_delays[MAX_SAMPLES * REGRESS_RUNS_RATIO];
+
+  /* This is an array of peer dispersions, being the skew and local
+     precision dispersion terms from sampling the peer */
+  double peer_dispersions[MAX_SAMPLES];
+
+  /* This array contains the root delays of each sample, in seconds */
+  double root_delays[MAX_SAMPLES];
+
+  /* This array contains the root dispersions of each sample at the
+     time of the measurements */
+  double root_dispersions[MAX_SAMPLES];
+};
+
+/* ================================================== */
+
+static void find_min_delay_sample(SST_Stats inst);
+static int get_buf_index(SST_Stats inst, int i);
+
+/* ================================================== */
+
+void
+SST_Initialise(void)
+{
+  logfileid = CNF_GetLogStatistics() ? LOG_FileOpen("statistics",
+      "   Date (UTC) Time     IP Address    Std dev'n Est offset  Offset sd  Diff freq   Est skew  Stress  Ns  Bs  Nr  Asym")
+    : -1;
+}
+
+/* ================================================== */
+
+void
+SST_Finalise(void)
+{
+}
+
+/* ================================================== */
+/* This function creates a new instance of the statistics handler */
+
+SST_Stats
+SST_CreateInstance(uint32_t refid, IPAddr *addr, int min_samples, int max_samples,
+                   double min_delay, double asymmetry)
+{
+  SST_Stats inst;
+  inst = MallocNew(struct SST_Stats_Record);
+
+  inst->max_samples = max_samples > 0 ? CLAMP(1, max_samples, MAX_SAMPLES) : MAX_SAMPLES;
+  inst->min_samples = CLAMP(1, min_samples, inst->max_samples);
+  inst->fixed_min_delay = min_delay;
+  inst->fixed_asymmetry = asymmetry;
+
+  SST_SetRefid(inst, refid, addr);
+  SST_ResetInstance(inst);
+
+  return inst;
+}
+
+/* ================================================== */
+/* This function deletes an instance of the statistics handler. */
+
+void
+SST_DeleteInstance(SST_Stats inst)
+{
+  Free(inst);
+}
+
+/* ================================================== */
+
+void
+SST_ResetInstance(SST_Stats inst)
+{
+  inst->n_samples = 0;
+  inst->runs_samples = 0;
+  inst->last_sample = 0;
+  inst->regression_ok = 0;
+  inst->best_single_sample = 0;
+  inst->min_delay_sample = 0;
+  inst->estimated_frequency = 0;
+  inst->estimated_frequency_sd = WORST_CASE_FREQ_BOUND;
+  inst->skew = WORST_CASE_FREQ_BOUND;
+  inst->estimated_offset = 0.0;
+  inst->estimated_offset_sd = WORST_CASE_STDDEV_BOUND;
+  UTI_ZeroTimespec(&inst->offset_time);
+  inst->std_dev = WORST_CASE_STDDEV_BOUND;
+  inst->nruns = 0;
+  inst->asymmetry_run = 0;
+  inst->asymmetry = 0.0;
+}
+
+/* ================================================== */
+
+void
+SST_SetRefid(SST_Stats inst, uint32_t refid, IPAddr *addr)
+{
+  inst->refid = refid;
+  inst->ip_addr = addr;
+}
+
+/* ================================================== */
+/* This function is called to prune the register down when it is full.
+   For now, just discard the oldest sample.  */
+
+static void
+prune_register(SST_Stats inst, int new_oldest)
+{
+  if (!new_oldest)
+    return;
+
+  assert(inst->n_samples >= new_oldest);
+  inst->n_samples -= new_oldest;
+  inst->runs_samples += new_oldest;
+  if (inst->runs_samples > inst->n_samples * (REGRESS_RUNS_RATIO - 1))
+    inst->runs_samples = inst->n_samples * (REGRESS_RUNS_RATIO - 1);
+  
+  assert(inst->n_samples + inst->runs_samples <= MAX_SAMPLES * REGRESS_RUNS_RATIO);
+
+  find_min_delay_sample(inst);
+}
+
+/* ================================================== */
+
+void
+SST_AccumulateSample(SST_Stats inst, NTP_Sample *sample)
+{
+  int n, m;
+
+  /* Make room for the new sample */
+  if (inst->n_samples > 0 &&
+      (inst->n_samples == MAX_SAMPLES || inst->n_samples == inst->max_samples)) {
+    prune_register(inst, 1);
+  }
+
+  /* Make sure it's newer than the last sample */
+  if (inst->n_samples &&
+      UTI_CompareTimespecs(&inst->sample_times[inst->last_sample], &sample->time) >= 0) {
+    LOG(LOGS_WARN, "Out of order sample detected, discarding history for %s",
+        inst->ip_addr ? UTI_IPToString(inst->ip_addr) : UTI_RefidToString(inst->refid));
+    SST_ResetInstance(inst);
+  }
+
+  n = inst->last_sample = (inst->last_sample + 1) %
+    (MAX_SAMPLES * REGRESS_RUNS_RATIO);
+  m = n % MAX_SAMPLES;
+
+  /* WE HAVE TO NEGATE OFFSET IN THIS CALL, IT IS HERE THAT THE SENSE OF OFFSET
+     IS FLIPPED */
+  inst->sample_times[n] = sample->time;
+  inst->offsets[n] = -sample->offset;
+  inst->orig_offsets[m] = -sample->offset;
+  inst->peer_delays[n] = sample->peer_delay;
+  inst->peer_dispersions[m] = sample->peer_dispersion;
+  inst->root_delays[m] = sample->root_delay;
+  inst->root_dispersions[m] = sample->root_dispersion;
+ 
+  if (inst->peer_delays[n] < inst->fixed_min_delay)
+    inst->peer_delays[n] = 2.0 * inst->fixed_min_delay - inst->peer_delays[n];
+
+  if (!inst->n_samples || inst->peer_delays[n] < inst->peer_delays[inst->min_delay_sample])
+    inst->min_delay_sample = n;
+
+  ++inst->n_samples;
+}
+
+/* ================================================== */
+/* Return index of the i-th sample in the sample_times and offset buffers,
+   i can be negative down to -runs_samples */
+
+static int
+get_runsbuf_index(SST_Stats inst, int i)
+{
+  return (unsigned int)(inst->last_sample + 2 * MAX_SAMPLES * REGRESS_RUNS_RATIO -
+      inst->n_samples + i + 1) % (MAX_SAMPLES * REGRESS_RUNS_RATIO);
+}
+
+/* ================================================== */
+/* Return index of the i-th sample in the other buffers */
+
+static int
+get_buf_index(SST_Stats inst, int i)
+{
+  return (unsigned int)(inst->last_sample + MAX_SAMPLES * REGRESS_RUNS_RATIO -
+      inst->n_samples + i + 1) % MAX_SAMPLES;
+}
+
+/* ================================================== */
+/* This function is used by both the regression routines to find the
+   time interval between each historical sample and the most recent
+   one */
+
+static void
+convert_to_intervals(SST_Stats inst, double *times_back)
+{
+  struct timespec *ts;
+  int i;
+
+  ts = &inst->sample_times[inst->last_sample];
+  for (i = -inst->runs_samples; i < inst->n_samples; i++) {
+    /* The entries in times_back[] should end up negative */
+    times_back[i] = UTI_DiffTimespecsToDouble(&inst->sample_times[get_runsbuf_index(inst, i)], ts);
+  }
+}
+
+/* ================================================== */
+
+static void
+find_best_sample_index(SST_Stats inst, double *times_back)
+{
+  /* With the value of skew that has been computed, see which of the
+     samples offers the tightest bound on root distance */
+
+  double root_distance, best_root_distance;
+  double elapsed;
+  int i, j, best_index;
+
+  if (!inst->n_samples)
+    return;
+
+  best_index = -1;
+  best_root_distance = DBL_MAX;
+
+  for (i = 0; i < inst->n_samples; i++) {
+    j = get_buf_index(inst, i);
+
+    elapsed = -times_back[i];
+    assert(elapsed >= 0.0);
+
+    root_distance = inst->root_dispersions[j] + elapsed * inst->skew + 0.5 * inst->root_delays[j];
+    if (root_distance < best_root_distance) {
+      best_root_distance = root_distance;
+      best_index = i;
+    }
+  }
+
+  assert(best_index >= 0);
+  inst->best_single_sample = best_index;
+}
+
+/* ================================================== */
+
+static void
+find_min_delay_sample(SST_Stats inst)
+{
+  int i, index;
+
+  inst->min_delay_sample = get_runsbuf_index(inst, -inst->runs_samples);
+
+  for (i = -inst->runs_samples + 1; i < inst->n_samples; i++) {
+    index = get_runsbuf_index(inst, i);
+    if (inst->peer_delays[index] < inst->peer_delays[inst->min_delay_sample])
+      inst->min_delay_sample = index;
+  }
+}
+
+/* ================================================== */
+/* This function estimates asymmetry of network jitter on the path to the
+   source as a slope of offset against network delay in multiple linear
+   regression.  If the asymmetry is significant and its sign doesn't change
+   frequently, the measured offsets (which are used later to estimate the
+   offset and frequency of the clock) are corrected to correspond to the
+   minimum network delay.  This can significantly improve the accuracy and
+   stability of the estimated offset and frequency. */
+
+static int
+estimate_asymmetry(double *times_back, double *offsets, double *delays, int n,
+                   double *asymmetry, int *asymmetry_run)
+{
+  double a;
+
+  /* Reset the counter when the regression fails or the sign changes */
+  if (!RGR_MultipleRegress(times_back, delays, offsets, n, &a) ||
+      a * *asymmetry_run < 0.0) {
+    *asymmetry = 0;
+    *asymmetry_run = 0.0;
+    return 0;
+  }
+
+  if (a <= -MIN_ASYMMETRY && *asymmetry_run > -MAX_ASYMMETRY_RUN)
+    (*asymmetry_run)--;
+  else if (a >= MIN_ASYMMETRY && *asymmetry_run < MAX_ASYMMETRY_RUN)
+    (*asymmetry_run)++;
+
+  if (abs(*asymmetry_run) < MIN_ASYMMETRY_RUN)
+    return 0;
+
+  *asymmetry = CLAMP(-MAX_ASYMMETRY, a, MAX_ASYMMETRY);
+
+  return 1;
+}
+
+/* ================================================== */
+
+static void
+correct_asymmetry(SST_Stats inst, double *times_back, double *offsets)
+{
+  double min_delay, delays[MAX_SAMPLES * REGRESS_RUNS_RATIO];
+  int i, n;
+
+  /* Check if the asymmetry was not specified to be zero */
+  if (inst->fixed_asymmetry == 0.0)
+    return;
+
+  min_delay = SST_MinRoundTripDelay(inst);
+  n = inst->runs_samples + inst->n_samples;
+
+  for (i = 0; i < n; i++)
+    delays[i] = inst->peer_delays[get_runsbuf_index(inst, i - inst->runs_samples)] -
+                min_delay;
+
+  if (fabs(inst->fixed_asymmetry) <= MAX_ASYMMETRY) {
+    inst->asymmetry = inst->fixed_asymmetry;
+  } else {
+    if (!estimate_asymmetry(times_back, offsets, delays, n,
+                            &inst->asymmetry, &inst->asymmetry_run))
+      return;
+  }
+
+  /* Correct the offsets */
+  for (i = 0; i < n; i++)
+    offsets[i] -= inst->asymmetry * delays[i];
+}
+
+/* ================================================== */
+
+/* This defines the assumed ratio between the standard deviation of
+   the samples and the peer distance as measured from the round trip
+   time.  E.g. a value of 4 means that we think the standard deviation
+   is four times the fluctuation  of the peer distance */
+
+#define SD_TO_DIST_RATIO 0.7
+
+/* ================================================== */
+/* This function runs the linear regression operation on the data.  It
+   finds the set of most recent samples that give the tightest
+   confidence interval for the frequency, and truncates the register
+   down to that number of samples */
+
+void
+SST_DoNewRegression(SST_Stats inst)
+{
+  double times_back[MAX_SAMPLES * REGRESS_RUNS_RATIO];
+  double offsets[MAX_SAMPLES * REGRESS_RUNS_RATIO];
+  double peer_distances[MAX_SAMPLES];
+  double weights[MAX_SAMPLES];
+
+  int degrees_of_freedom;
+  int best_start, times_back_start;
+  double est_intercept, est_slope, est_var, est_intercept_sd, est_slope_sd;
+  int i, j, nruns;
+  double min_distance, median_distance;
+  double sd_weight, sd;
+  double old_skew, old_freq, stress;
+  double precision;
+
+  convert_to_intervals(inst, times_back + inst->runs_samples);
+
+  if (inst->n_samples > 0) {
+    for (i = -inst->runs_samples; i < inst->n_samples; i++) {
+      offsets[i + inst->runs_samples] = inst->offsets[get_runsbuf_index(inst, i)];
+    }
+  
+    for (i = 0, min_distance = DBL_MAX; i < inst->n_samples; i++) {
+      j = get_buf_index(inst, i);
+      peer_distances[i] = 0.5 * inst->peer_delays[get_runsbuf_index(inst, i)] +
+                          inst->peer_dispersions[j];
+      if (peer_distances[i] < min_distance) {
+        min_distance = peer_distances[i];
+      }
+    }
+
+    /* And now, work out the weight vector */
+
+    precision = LCL_GetSysPrecisionAsQuantum();
+    median_distance = RGR_FindMedian(peer_distances, inst->n_samples);
+
+    sd = (median_distance - min_distance) / SD_TO_DIST_RATIO;
+    sd = CLAMP(precision, sd, min_distance);
+    min_distance += precision;
+
+    for (i=0; i<inst->n_samples; i++) {
+      sd_weight = 1.0;
+      if (peer_distances[i] > min_distance)
+        sd_weight += (peer_distances[i] - min_distance) / sd;
+      weights[i] = SQUARE(sd_weight);
+    }
+  }
+
+  correct_asymmetry(inst, times_back, offsets);
+
+  inst->regression_ok = RGR_FindBestRegression(times_back + inst->runs_samples,
+                                         offsets + inst->runs_samples, weights,
+                                         inst->n_samples, inst->runs_samples,
+                                         inst->min_samples,
+                                         &est_intercept, &est_slope, &est_var,
+                                         &est_intercept_sd, &est_slope_sd,
+                                         &best_start, &nruns, &degrees_of_freedom);
+
+  if (inst->regression_ok) {
+
+    old_skew = inst->skew;
+    old_freq = inst->estimated_frequency;
+  
+    inst->estimated_frequency = est_slope;
+    inst->estimated_frequency_sd = CLAMP(MIN_SKEW, est_slope_sd, MAX_SKEW);
+    inst->skew = est_slope_sd * RGR_GetTCoef(degrees_of_freedom);
+    inst->estimated_offset = est_intercept;
+    inst->offset_time = inst->sample_times[inst->last_sample];
+    inst->estimated_offset_sd = est_intercept_sd;
+    inst->std_dev = MAX(MIN_STDDEV, sqrt(est_var));
+    inst->nruns = nruns;
+
+    inst->skew = CLAMP(MIN_SKEW, inst->skew, MAX_SKEW);
+    stress = fabs(old_freq - inst->estimated_frequency) / old_skew;
+
+    DEBUG_LOG("off=%e freq=%e skew=%e n=%d bs=%d runs=%d asym=%f arun=%d",
+              inst->estimated_offset, inst->estimated_frequency, inst->skew,
+              inst->n_samples, best_start, inst->nruns,
+              inst->asymmetry, inst->asymmetry_run);
+
+    if (logfileid != -1) {
+      LOG_FileWrite(logfileid, "%s %-15s %10.3e %10.3e %10.3e %10.3e %10.3e %7.1e %3d %3d %3d %5.2f",
+              UTI_TimeToLogForm(inst->offset_time.tv_sec),
+              inst->ip_addr ? UTI_IPToString(inst->ip_addr) : UTI_RefidToString(inst->refid),
+              inst->std_dev,
+              inst->estimated_offset, inst->estimated_offset_sd,
+              inst->estimated_frequency, inst->skew, stress,
+              inst->n_samples, best_start, inst->nruns,
+              inst->asymmetry);
+    }
+
+    times_back_start = inst->runs_samples + best_start;
+    prune_register(inst, best_start);
+  } else {
+    inst->estimated_frequency_sd = WORST_CASE_FREQ_BOUND;
+    inst->skew = WORST_CASE_FREQ_BOUND;
+    inst->estimated_offset_sd = WORST_CASE_STDDEV_BOUND;
+    inst->std_dev = WORST_CASE_STDDEV_BOUND;
+    inst->nruns = 0;
+
+    if (inst->n_samples > 0) {
+      inst->estimated_offset = inst->offsets[inst->last_sample];
+      inst->offset_time = inst->sample_times[inst->last_sample];
+    } else {
+      inst->estimated_offset = 0.0;
+      UTI_ZeroTimespec(&inst->offset_time);
+    }
+
+    times_back_start = 0;
+  }
+
+  find_best_sample_index(inst, times_back + times_back_start);
+
+}
+
+/* ================================================== */
+/* Return the assumed worst case range of values that this source's
+   frequency lies within.  Frequency is defined as the amount of time
+   the local clock gains relative to the source per unit local clock
+   time. */
+void
+SST_GetFrequencyRange(SST_Stats inst,
+                      double *lo, double *hi)
+{
+  double freq, skew;
+  freq = inst->estimated_frequency;
+  skew = inst->skew;
+  *lo = freq - skew;
+  *hi = freq + skew;
+
+  /* This function is currently used only to determine the values of delta
+     and epsilon in the ntp_core module. Limit the skew to a reasonable maximum
+     to avoid failing the dispersion test too easily. */
+  if (skew > WORST_CASE_FREQ_BOUND) {
+    *lo = -WORST_CASE_FREQ_BOUND;
+    *hi = WORST_CASE_FREQ_BOUND;
+  }
+}
+
+/* ================================================== */
+
+void
+SST_GetSelectionData(SST_Stats inst, struct timespec *now,
+                     double *offset_lo_limit,
+                     double *offset_hi_limit,
+                     double *root_distance,
+                     double *std_dev,
+                     double *first_sample_ago,
+                     double *last_sample_ago,
+                     int *select_ok)
+{
+  double offset, sample_elapsed;
+  int i, j;
+  
+  if (!inst->n_samples) {
+    *select_ok = 0;
+    return;
+  }
+
+  i = get_runsbuf_index(inst, inst->best_single_sample);
+  j = get_buf_index(inst, inst->best_single_sample);
+
+  *std_dev = inst->std_dev;
+
+  sample_elapsed = fabs(UTI_DiffTimespecsToDouble(now, &inst->sample_times[i]));
+  offset = inst->offsets[i] + sample_elapsed * inst->estimated_frequency;
+  *root_distance = 0.5 * inst->root_delays[j] +
+    inst->root_dispersions[j] + sample_elapsed * inst->skew;
+
+  *offset_lo_limit = offset - *root_distance;
+  *offset_hi_limit = offset + *root_distance;
+
+#if 0
+  double average_offset, elapsed;
+  int average_ok;
+  /* average_ok ignored for now */
+  elapsed = UTI_DiffTimespecsToDouble(now, &inst->offset_time);
+  average_offset = inst->estimated_offset + inst->estimated_frequency * elapsed;
+  if (fabs(average_offset - offset) <=
+      inst->peer_dispersions[j] + 0.5 * inst->peer_delays[i]) {
+    average_ok = 1;
+  } else {
+    average_ok = 0;
+  }
+#endif
+
+  i = get_runsbuf_index(inst, 0);
+  *first_sample_ago = UTI_DiffTimespecsToDouble(now, &inst->sample_times[i]);
+  i = get_runsbuf_index(inst, inst->n_samples - 1);
+  *last_sample_ago = UTI_DiffTimespecsToDouble(now, &inst->sample_times[i]);
+
+  *select_ok = inst->regression_ok;
+
+  /* If maxsamples is too small to have a successful regression, enable the
+     selection as a special case for a fast update/print-once reference mode */
+  if (!*select_ok && inst->n_samples < MIN_SAMPLES_FOR_REGRESS &&
+      inst->n_samples == inst->max_samples) {
+    *std_dev = CNF_GetMaxJitter();
+    *select_ok = 1;
+  }
+
+  DEBUG_LOG("n=%d off=%f dist=%f sd=%f first_ago=%f last_ago=%f selok=%d",
+            inst->n_samples, offset, *root_distance, *std_dev,
+            *first_sample_ago, *last_sample_ago, *select_ok);
+}
+
+/* ================================================== */
+
+void
+SST_GetTrackingData(SST_Stats inst, struct timespec *ref_time,
+                    double *average_offset, double *offset_sd,
+                    double *frequency, double *frequency_sd, double *skew,
+                    double *root_delay, double *root_dispersion)
+{
+  int i, j;
+  double elapsed_sample;
+
+  assert(inst->n_samples > 0);
+
+  i = get_runsbuf_index(inst, inst->best_single_sample);
+  j = get_buf_index(inst, inst->best_single_sample);
+
+  *ref_time = inst->offset_time;
+  *average_offset = inst->estimated_offset;
+  *offset_sd = inst->estimated_offset_sd;
+  *frequency = inst->estimated_frequency;
+  *frequency_sd = inst->estimated_frequency_sd;
+  *skew = inst->skew;
+  *root_delay = inst->root_delays[j];
+
+  elapsed_sample = UTI_DiffTimespecsToDouble(&inst->offset_time, &inst->sample_times[i]);
+  *root_dispersion = inst->root_dispersions[j] + inst->skew * elapsed_sample + *offset_sd;
+
+  DEBUG_LOG("n=%d off=%f offsd=%f freq=%e freqsd=%e skew=%e delay=%f disp=%f",
+            inst->n_samples, *average_offset, *offset_sd,
+            *frequency, *frequency_sd, *skew, *root_delay, *root_dispersion);
+}
+
+/* ================================================== */
+
+void
+SST_SlewSamples(SST_Stats inst, struct timespec *when, double dfreq, double doffset)
+{
+  int m, i;
+  double delta_time;
+  struct timespec *sample, prev;
+  double prev_offset, prev_freq;
+
+  if (!inst->n_samples)
+    return;
+
+  for (m = -inst->runs_samples; m < inst->n_samples; m++) {
+    i = get_runsbuf_index(inst, m);
+    sample = &inst->sample_times[i];
+    prev = *sample;
+    UTI_AdjustTimespec(sample, when, sample, &delta_time, dfreq, doffset);
+    inst->offsets[i] += delta_time;
+  }
+
+  /* Update the regression estimates */
+  prev = inst->offset_time;
+  prev_offset = inst->estimated_offset;
+  prev_freq = inst->estimated_frequency;
+  UTI_AdjustTimespec(&inst->offset_time, when, &inst->offset_time,
+      &delta_time, dfreq, doffset);
+  inst->estimated_offset += delta_time;
+  inst->estimated_frequency = (inst->estimated_frequency - dfreq) / (1.0 - dfreq);
+
+  DEBUG_LOG("n=%d m=%d old_off_time=%s new=%s old_off=%f new_off=%f old_freq=%.3f new_freq=%.3f",
+            inst->n_samples, inst->runs_samples,
+            UTI_TimespecToString(&prev), UTI_TimespecToString(&inst->offset_time),
+            prev_offset, inst->estimated_offset,
+            1.0e6 * prev_freq, 1.0e6 * inst->estimated_frequency);
+}
+
+/* ================================================== */
+
+void
+SST_CorrectOffset(SST_Stats inst, double doffset)
+{
+  int i;
+
+  if (!inst->n_samples)
+    return;
+
+  for (i = -inst->runs_samples; i < inst->n_samples; i++)
+    inst->offsets[get_runsbuf_index(inst, i)] += doffset;
+
+  inst->estimated_offset += doffset;
+}
+
+/* ================================================== */
+
+void 
+SST_AddDispersion(SST_Stats inst, double dispersion)
+{
+  int m, i;
+
+  for (m = 0; m < inst->n_samples; m++) {
+    i = get_buf_index(inst, m);
+    inst->root_dispersions[i] += dispersion;
+    inst->peer_dispersions[i] += dispersion;
+  }
+}
+
+/* ================================================== */
+
+double
+SST_PredictOffset(SST_Stats inst, struct timespec *when)
+{
+  double elapsed;
+  
+  if (inst->n_samples < MIN_SAMPLES_FOR_REGRESS) {
+    /* We don't have any useful statistics, and presumably the poll
+       interval is minimal.  We can't do any useful prediction other
+       than use the latest sample or zero if we don't have any samples */
+    if (inst->n_samples > 0) {
+      return inst->offsets[inst->last_sample];
+    } else {
+      return 0.0;
+    }
+  } else {
+    elapsed = UTI_DiffTimespecsToDouble(when, &inst->offset_time);
+    return inst->estimated_offset + elapsed * inst->estimated_frequency;
+  }
+
+}
+
+/* ================================================== */
+
+double
+SST_MinRoundTripDelay(SST_Stats inst)
+{
+  if (inst->fixed_min_delay > 0.0)
+    return inst->fixed_min_delay;
+
+  if (!inst->n_samples)
+    return DBL_MAX;
+
+  return inst->peer_delays[inst->min_delay_sample];
+}
+
+/* ================================================== */
+
+int
+SST_GetDelayTestData(SST_Stats inst, struct timespec *sample_time,
+                     double *last_sample_ago, double *predicted_offset,
+                     double *min_delay, double *skew, double *std_dev)
+{
+  if (inst->n_samples < 6)
+    return 0;
+
+  *last_sample_ago = UTI_DiffTimespecsToDouble(sample_time, &inst->offset_time);
+  *predicted_offset = inst->estimated_offset +
+                      *last_sample_ago * inst->estimated_frequency;
+  *min_delay = SST_MinRoundTripDelay(inst);
+  *skew = inst->skew;
+  *std_dev = inst->std_dev;
+
+  return 1;
+}
+
+/* ================================================== */
+/* This is used to save the register to a file, so that we can reload
+   it after restarting the daemon */
+
+int
+SST_SaveToFile(SST_Stats inst, FILE *out)
+{
+  int m, i, j;
+
+  if (inst->n_samples < 1)
+    return 0;
+
+  if (fprintf(out, "%d %d\n", inst->n_samples, inst->asymmetry_run) < 0)
+    return 0;
+
+  for(m = 0; m < inst->n_samples; m++) {
+    i = get_runsbuf_index(inst, m);
+    j = get_buf_index(inst, m);
+
+    if (fprintf(out, "%s %.6e %.6e %.6e %.6e %.6e %.6e\n",
+                UTI_TimespecToString(&inst->sample_times[i]),
+                inst->offsets[i], inst->orig_offsets[j],
+                inst->peer_delays[i], inst->peer_dispersions[j],
+                inst->root_delays[j], inst->root_dispersions[j]) < 0)
+      return 0;
+  }
+
+  return 1;
+}
+
+/* ================================================== */
+/* This is used to reload samples from a file */
+
+int
+SST_LoadFromFile(SST_Stats inst, FILE *in)
+{
+  int i, n_samples, arun;
+  struct timespec now;
+  double sample_time;
+  char line[256];
+
+  if (!fgets(line, sizeof (line), in) ||
+      sscanf(line, "%d %d", &n_samples, &arun) != 2 ||
+      n_samples < 1 || n_samples > MAX_SAMPLES)
+    return 0;
+
+  SST_ResetInstance(inst);
+
+  LCL_ReadCookedTime(&now, NULL);
+
+  for (i = 0; i < n_samples; i++) {
+    if (!fgets(line, sizeof (line), in) ||
+        sscanf(line, "%lf %lf %lf %lf %lf %lf %lf",
+               &sample_time, &inst->offsets[i], &inst->orig_offsets[i],
+               &inst->peer_delays[i], &inst->peer_dispersions[i],
+               &inst->root_delays[i], &inst->root_dispersions[i]) != 7)
+      return 0;
+
+    if (!UTI_IsTimeOffsetSane(&now, sample_time - UTI_TimespecToDouble(&now)))
+      return 0;
+
+    /* Some resolution is lost in the double format, but that's ok */
+    UTI_DoubleToTimespec(sample_time, &inst->sample_times[i]);
+
+    /* Make sure the samples are sane and they are in order */
+    if (!UTI_IsTimeOffsetSane(&inst->sample_times[i], -inst->offsets[i]) ||
+        UTI_CompareTimespecs(&now, &inst->sample_times[i]) < 0 ||
+        !(fabs(inst->peer_delays[i]) < 1.0e6 && fabs(inst->peer_dispersions[i]) < 1.0e6 &&
+          fabs(inst->root_delays[i]) < 1.0e6 && fabs(inst->root_dispersions[i]) < 1.0e6) ||
+        (i > 0 && UTI_CompareTimespecs(&inst->sample_times[i],
+                                       &inst->sample_times[i - 1]) <= 0))
+      return 0;
+  }
+
+  inst->n_samples = n_samples;
+  inst->last_sample = inst->n_samples - 1;
+  inst->asymmetry_run = CLAMP(-MAX_ASYMMETRY_RUN, arun, MAX_ASYMMETRY_RUN);
+
+  find_min_delay_sample(inst);
+  SST_DoNewRegression(inst);
+
+  return 1;
+}
+
+/* ================================================== */
+
+void
+SST_DoSourceReport(SST_Stats inst, RPT_SourceReport *report, struct timespec *now)
+{
+  int i, j;
+  struct timespec last_sample_time;
+
+  if (inst->n_samples > 0) {
+    i = get_runsbuf_index(inst, inst->n_samples - 1);
+    j = get_buf_index(inst, inst->n_samples - 1);
+    report->orig_latest_meas = inst->orig_offsets[j];
+    report->latest_meas = inst->offsets[i];
+    report->latest_meas_err = 0.5*inst->root_delays[j] + inst->root_dispersions[j];
+
+    /* Align the sample time to reduce the leak of the receive timestamp */
+    last_sample_time = inst->sample_times[i];
+    last_sample_time.tv_nsec = 0;
+    report->latest_meas_ago = UTI_DiffTimespecsToDouble(now, &last_sample_time);
+  } else {
+    report->latest_meas_ago = (uint32_t)-1;
+    report->orig_latest_meas = 0;
+    report->latest_meas = 0;
+    report->latest_meas_err = 0;
+    report->stratum = 0;
+  }
+}
+
+/* ================================================== */
+
+int
+SST_Samples(SST_Stats inst)
+{
+  return inst->n_samples;
+}
+
+/* ================================================== */
+
+int
+SST_GetMinSamples(SST_Stats inst)
+{
+  return inst->min_samples;
+}
+
+/* ================================================== */
+
+void
+SST_DoSourcestatsReport(SST_Stats inst, RPT_SourcestatsReport *report, struct timespec *now)
+{
+  double dspan;
+  double elapsed, sample_elapsed;
+  int bi, bj;
+
+  report->n_samples = inst->n_samples;
+  report->n_runs = inst->nruns;
+
+  if (inst->n_samples > 0) {
+    bi = get_runsbuf_index(inst, inst->best_single_sample);
+    bj = get_buf_index(inst, inst->best_single_sample);
+
+    dspan = UTI_DiffTimespecsToDouble(&inst->sample_times[inst->last_sample],
+                                      &inst->sample_times[get_runsbuf_index(inst, 0)]);
+    elapsed = UTI_DiffTimespecsToDouble(now, &inst->offset_time);
+    sample_elapsed = UTI_DiffTimespecsToDouble(now, &inst->sample_times[bi]);
+
+    report->span_seconds = round(dspan);
+    report->est_offset = inst->estimated_offset + elapsed * inst->estimated_frequency;
+    report->est_offset_err = inst->estimated_offset_sd + sample_elapsed * inst->skew +
+                             (0.5 * inst->root_delays[bj] + inst->root_dispersions[bj]);
+  } else {
+    report->span_seconds = 0;
+    report->est_offset = 0;
+    report->est_offset_err = 0;
+  }
+
+  report->resid_freq_ppm = 1.0e6 * inst->estimated_frequency;
+  report->skew_ppm = 1.0e6 * inst->skew;
+  report->sd = inst->std_dev;
+}
+
+/* ================================================== */
+
+double
+SST_GetJitterAsymmetry(SST_Stats inst)
+{
+  return inst->asymmetry;
+}
+
+/* ================================================== */