// 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);}EXPORT_SYMBOL(minmax_running_min);