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Diffstat (limited to 'lib/win_minmax.c')
| -rw-r--r-- | lib/win_minmax.c | 99 |
1 files changed, 99 insertions, 0 deletions
diff --git a/lib/win_minmax.c b/lib/win_minmax.c new file mode 100644 index 0000000000..ec10506834 --- /dev/null +++ b/lib/win_minmax.c @@ -0,0 +1,99 @@ +// SPDX-License-Identifier: GPL-2.0 +/* + * lib/minmax.c: windowed min/max tracker + * + * Kathleen Nichols' algorithm for tracking the minimum (or maximum) + * value of a data stream over some fixed time interval. (E.g., + * the minimum RTT over the past five minutes.) It uses constant + * space and constant time per update yet almost always delivers + * the same minimum as an implementation that has to keep all the + * data in the window. + * + * The algorithm keeps track of the best, 2nd best & 3rd best min + * values, maintaining an invariant that the measurement time of + * the n'th best >= n-1'th best. It also makes sure that the three + * values are widely separated in the time window since that bounds + * the worse case error when that data is monotonically increasing + * over the window. + * + * Upon getting a new min, we can forget everything earlier because + * it has no value - the new min is <= everything else in the window + * by definition and it's the most recent. So we restart fresh on + * every new min and overwrites 2nd & 3rd choices. The same property + * holds for 2nd & 3rd best. + */ +#include <linux/module.h> +#include <linux/win_minmax.h> + +/* As time advances, update the 1st, 2nd, and 3rd choices. */ +static u32 minmax_subwin_update(struct minmax *m, u32 win, + const struct minmax_sample *val) +{ + u32 dt = val->t - m->s[0].t; + + if (unlikely(dt > win)) { + /* + * Passed entire window without a new val so make 2nd + * choice the new val & 3rd choice the new 2nd choice. + * we may have to iterate this since our 2nd choice + * may also be outside the window (we checked on entry + * that the third choice was in the window). + */ + m->s[0] = m->s[1]; + m->s[1] = m->s[2]; + m->s[2] = *val; + if (unlikely(val->t - m->s[0].t > win)) { + m->s[0] = m->s[1]; + m->s[1] = m->s[2]; + m->s[2] = *val; + } + } else if (unlikely(m->s[1].t == m->s[0].t) && dt > win/4) { + /* + * We've passed a quarter of the window without a new val + * so take a 2nd choice from the 2nd quarter of the window. + */ + m->s[2] = m->s[1] = *val; + } else if (unlikely(m->s[2].t == m->s[1].t) && dt > win/2) { + /* + * We've passed half the window without finding a new val + * so take a 3rd choice from the last half of the window + */ + m->s[2] = *val; + } + return m->s[0].v; +} + +/* Check if new measurement updates the 1st, 2nd or 3rd choice max. */ +u32 minmax_running_max(struct minmax *m, u32 win, u32 t, u32 meas) +{ + struct minmax_sample val = { .t = t, .v = meas }; + + if (unlikely(val.v >= m->s[0].v) || /* found new max? */ + unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ + return minmax_reset(m, t, meas); /* forget earlier samples */ + + if (unlikely(val.v >= m->s[1].v)) + m->s[2] = m->s[1] = val; + else if (unlikely(val.v >= m->s[2].v)) + m->s[2] = val; + + return minmax_subwin_update(m, win, &val); +} +EXPORT_SYMBOL(minmax_running_max); + +/* Check if new measurement updates the 1st, 2nd or 3rd choice min. */ +u32 minmax_running_min(struct minmax *m, u32 win, u32 t, u32 meas) +{ + struct minmax_sample val = { .t = t, .v = meas }; + + if (unlikely(val.v <= m->s[0].v) || /* found new min? */ + unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ + return minmax_reset(m, t, meas); /* forget earlier samples */ + + if (unlikely(val.v <= m->s[1].v)) + m->s[2] = m->s[1] = val; + else if (unlikely(val.v <= m->s[2].v)) + m->s[2] = val; + + return minmax_subwin_update(m, win, &val); +} |