100 lines · c
1// SPDX-License-Identifier: GPL-2.02/*3 * lib/minmax.c: windowed min/max tracker4 *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 constant8 * space and constant time per update yet almost always delivers9 * the same minimum as an implementation that has to keep all the10 * data in the window.11 *12 * The algorithm keeps track of the best, 2nd best & 3rd best min13 * values, maintaining an invariant that the measurement time of14 * the n'th best >= n-1'th best. It also makes sure that the three15 * values are widely separated in the time window since that bounds16 * the worse case error when that data is monotonically increasing17 * over the window.18 *19 * Upon getting a new min, we can forget everything earlier because20 * it has no value - the new min is <= everything else in the window21 * by definition and it's the most recent. So we restart fresh on22 * every new min and overwrites 2nd & 3rd choices. The same property23 * 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. */29static u32 minmax_subwin_update(struct minmax *m, u32 win,30 const struct minmax_sample *val)31{32 u32 dt = val->t - m->s[0].t;33 34 if (unlikely(dt > win)) {35 /*36 * Passed entire window without a new val so make 2nd37 * choice the new val & 3rd choice the new 2nd choice.38 * we may have to iterate this since our 2nd choice39 * may also be outside the window (we checked on entry40 * that the third choice was in the window).41 */42 m->s[0] = m->s[1];43 m->s[1] = m->s[2];44 m->s[2] = *val;45 if (unlikely(val->t - m->s[0].t > win)) {46 m->s[0] = m->s[1];47 m->s[1] = m->s[2];48 m->s[2] = *val;49 }50 } 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 val53 * so take a 2nd choice from the 2nd quarter of the window.54 */55 m->s[2] = m->s[1] = *val;56 } 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 val59 * so take a 3rd choice from the last half of the window60 */61 m->s[2] = *val;62 }63 return m->s[0].v;64}65 66/* Check if new measurement updates the 1st, 2nd or 3rd choice max. */67u32 minmax_running_max(struct minmax *m, u32 win, u32 t, u32 meas)68{69 struct minmax_sample val = { .t = t, .v = meas };70 71 if (unlikely(val.v >= m->s[0].v) || /* found new max? */72 unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */73 return minmax_reset(m, t, meas); /* forget earlier samples */74 75 if (unlikely(val.v >= m->s[1].v))76 m->s[2] = m->s[1] = val;77 else if (unlikely(val.v >= m->s[2].v))78 m->s[2] = val;79 80 return minmax_subwin_update(m, win, &val);81}82EXPORT_SYMBOL(minmax_running_max);83 84/* Check if new measurement updates the 1st, 2nd or 3rd choice min. */85u32 minmax_running_min(struct minmax *m, u32 win, u32 t, u32 meas)86{87 struct minmax_sample val = { .t = t, .v = meas };88 89 if (unlikely(val.v <= m->s[0].v) || /* found new min? */90 unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */91 return minmax_reset(m, t, meas); /* forget earlier samples */92 93 if (unlikely(val.v <= m->s[1].v))94 m->s[2] = m->s[1] = val;95 else if (unlikely(val.v <= m->s[2].v))96 m->s[2] = val;97 98 return minmax_subwin_update(m, win, &val);99}100