Line data    Source code

       1             : // SPDX-License-Identifier: GPL-2.0
       2             : /**
       3             :  * lib/minmax.c: windowed min/max tracker
       4             :  *
       5             :  * Kathleen Nichols' algorithm for tracking the minimum (or maximum)
       6             :  * value of a data stream over some fixed time interval.  (E.g.,
       7             :  * the minimum RTT over the past five minutes.) It uses constant
       8             :  * space and constant time per update yet almost always delivers
       9             :  * the same minimum as an implementation that has to keep all the
      10             :  * data in the window.
      11             :  *
      12             :  * The algorithm keeps track of the best, 2nd best & 3rd best min
      13             :  * values, maintaining an invariant that the measurement time of
      14             :  * the n'th best >= n-1'th best. It also makes sure that the three
      15             :  * values are widely separated in the time window since that bounds
      16             :  * the worse case error when that data is monotonically increasing
      17             :  * over the window.
      18             :  *
      19             :  * Upon getting a new min, we can forget everything earlier because
      20             :  * it has no value - the new min is <= everything else in the window
      21             :  * by definition and it's the most recent. So we restart fresh on
      22             :  * every new min and overwrites 2nd & 3rd choices. The same property
      23             :  * holds for 2nd & 3rd best.
      24             :  */
      25             : #include <linux/module.h>
      26             : #include <linux/win_minmax.h>
      27             : 
      28             : /* As time advances, update the 1st, 2nd, and 3rd choices. */
      29         238 : static u32 minmax_subwin_update(struct minmax *m, u32 win,
      30             :                                 const struct minmax_sample *val)
      31             : {
      32         238 :         u32 dt = val->t - m->s[0].t;
      33             : 
      34         238 :         if (unlikely(dt > win)) {
      35             :                 /*
      36             :                  * Passed entire window without a new val so make 2nd
      37             :                  * choice the new val & 3rd choice the new 2nd choice.
      38             :                  * we may have to iterate this since our 2nd choice
      39             :                  * may also be outside the window (we checked on entry
      40             :                  * that the third choice was in the window).
      41             :                  */
      42           0 :                 m->s[0] = m->s[1];
      43           0 :                 m->s[1] = m->s[2];
      44           0 :                 m->s[2] = *val;
      45           0 :                 if (unlikely(val->t - m->s[0].t > win)) {
      46           0 :                         m->s[0] = m->s[1];
      47           0 :                         m->s[1] = m->s[2];
      48           0 :                         m->s[2] = *val;
      49             :                 }
      50         238 :         } else if (unlikely(m->s[1].t == m->s[0].t) && dt > win/4) {
      51             :                 /*
      52             :                  * We've passed a quarter of the window without a new val
      53             :                  * so take a 2nd choice from the 2nd quarter of the window.
      54             :                  */
      55           0 :                 m->s[2] = m->s[1] = *val;
      56         238 :         } else if (unlikely(m->s[2].t == m->s[1].t) && dt > win/2) {
      57             :                 /*
      58             :                  * We've passed half the window without finding a new val
      59             :                  * so take a 3rd choice from the last half of the window
      60             :                  */
      61           0 :                 m->s[2] = *val;
      62             :         }
      63         238 :         return m->s[0].v;
      64             : }
      65             : 
      66             : /* Check if new measurement updates the 1st, 2nd or 3rd choice max. */
      67           0 : u32 minmax_running_max(struct minmax *m, u32 win, u32 t, u32 meas)
      68             : {
      69           0 :         struct minmax_sample val = { .t = t, .v = meas };
      70             : 
      71           0 :         if (unlikely(val.v >= m->s[0].v) ||         /* found new max? */
      72           0 :             unlikely(val.t - m->s[2].t > win))      /* nothing left in window? */
      73           0 :                 return minmax_reset(m, t, meas);  /* forget earlier samples */
      74             : 
      75           0 :         if (unlikely(val.v >= m->s[1].v))
      76           0 :                 m->s[2] = m->s[1] = val;
      77           0 :         else if (unlikely(val.v >= m->s[2].v))
      78           0 :                 m->s[2] = val;
      79             : 
      80           0 :         return minmax_subwin_update(m, win, &val);
      81             : }
      82             : EXPORT_SYMBOL(minmax_running_max);
      83             : 
      84             : /* Check if new measurement updates the 1st, 2nd or 3rd choice min. */
      85         257 : u32 minmax_running_min(struct minmax *m, u32 win, u32 t, u32 meas)
      86             : {
      87         257 :         struct minmax_sample val = { .t = t, .v = meas };
      88             : 
      89         257 :         if (unlikely(val.v <= m->s[0].v) ||         /* found new min? */
      90         238 :             unlikely(val.t - m->s[2].t > win))      /* nothing left in window? */
      91          19 :                 return minmax_reset(m, t, meas);  /* forget earlier samples */
      92             : 
      93         238 :         if (unlikely(val.v <= m->s[1].v))
      94           0 :                 m->s[2] = m->s[1] = val;
      95         238 :         else if (unlikely(val.v <= m->s[2].v))
      96           0 :                 m->s[2] = val;
      97             : 
      98         238 :         return minmax_subwin_update(m, win, &val);
      99             : }