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| 1 | +#ifndef _HAPROXY_WINDOW_FILTER_H |
| 2 | +#define _HAPROXY_WINDOW_FILTER_H |
| 3 | + |
| 4 | +/* Kathleen Nichols' algorithm to track the maximum values of a data type during |
| 5 | + * a fixed time interval. This algorithm makes usage of three samples to track |
| 6 | + * the best, second best and third best values with 1st >= 2nd >= 3rd as |
| 7 | + * invariant. |
| 8 | + * |
| 9 | + * This code is used in Linux kernel in linux/win_minmax.c to track both |
| 10 | + * minimal and maximum values. |
| 11 | + * |
| 12 | + * Here the code has been adapted to track 64 bits values and only their |
| 13 | + * maximum. |
| 14 | + * |
| 15 | + * Note that these windowed filters are used by BBR to filter the maximum |
| 16 | + * estimated bandwidth with counters as time values. A length has been |
| 17 | + * added to simulate the fixed time interval with counter which are |
| 18 | + * monotonically increasing. |
| 19 | + */ |
| 20 | + |
| 21 | +/* Windowed filter sample */ |
| 22 | +struct wf_smp { |
| 23 | + uint64_t v; |
| 24 | + uint32_t t; |
| 25 | +}; |
| 26 | + |
| 27 | +/* Windowed filter */ |
| 28 | +struct wf { |
| 29 | + size_t len; |
| 30 | + struct wf_smp smp[3]; |
| 31 | +}; |
| 32 | + |
| 33 | +/* Reset all the <wf> windowed filter samples with <v> and <t> as value and |
| 34 | + * time value respectively. |
| 35 | + */ |
| 36 | +static inline uint64_t wf_reset(struct wf *wf, uint64_t v, uint32_t t) |
| 37 | +{ |
| 38 | + struct wf_smp smp = { .v = v, .t = t }; |
| 39 | + |
| 40 | + wf->smp[2] = wf->smp[1] = wf->smp[0] = smp; |
| 41 | + |
| 42 | + return wf->smp[0].v; |
| 43 | +} |
| 44 | + |
| 45 | +/* Initialize <wf> windowed filter to track maximum values, with <len> as |
| 46 | + * length and <v> and <t> as value and time value respectively. |
| 47 | + */ |
| 48 | +static inline void wf_init(struct wf *wf, size_t len, uint64_t v, uint32_t t) |
| 49 | +{ |
| 50 | + wf->len = len; |
| 51 | + wf_reset(wf, v, t); |
| 52 | +} |
| 53 | + |
| 54 | +/* Similar to minmax_running_max() Linux kernel function to update the best |
| 55 | + * estimation of <wf> windowed filted with <v> and <t> as value and time value |
| 56 | + * respectively |
| 57 | + */ |
| 58 | +static inline uint64_t wf_max_update(struct wf *wf, uint64_t v, uint32_t t) |
| 59 | +{ |
| 60 | + uint64_t delta_t; |
| 61 | + struct wf_smp smp = { .v = v, .t = t }; |
| 62 | + |
| 63 | + /* Reset all estimates if they have not yet been initialized, if new |
| 64 | + sample is a new best, or if the newest recorded estimate is too |
| 65 | + old. */ |
| 66 | + if (unlikely(v > wf->smp[0].v) || unlikely(t - wf->smp[2].t > wf->len)) |
| 67 | + return wf_reset(wf, v, t); |
| 68 | + |
| 69 | + if (unlikely(v > wf->smp[1].v)) |
| 70 | + wf->smp[2] = wf->smp[1] = smp; |
| 71 | + else if (unlikely(v > wf->smp[2].v)) |
| 72 | + wf->smp[2] = smp; |
| 73 | + |
| 74 | + delta_t = t - wf->smp[0].t; |
| 75 | + /* From here, similar to minmax_subwin_update() from Linux kernel. */ |
| 76 | + if (unlikely(delta_t > wf->len)) { |
| 77 | + wf->smp[0] = wf->smp[1]; |
| 78 | + wf->smp[1] = wf->smp[2]; |
| 79 | + wf->smp[2].v = v; |
| 80 | + wf->smp[2].t = t; |
| 81 | + |
| 82 | + if (unlikely(t - wf->smp[0].t > wf->len)) { |
| 83 | + wf->smp[0] = wf->smp[1]; |
| 84 | + wf->smp[1] = wf->smp[2]; |
| 85 | + } |
| 86 | + } else if (unlikely(wf->smp[1].v == wf->smp[0].v) && delta_t > wf->len / 4) { |
| 87 | + wf->smp[2].v = v; |
| 88 | + wf->smp[2].t = t; |
| 89 | + wf->smp[1] = wf->smp[2]; |
| 90 | + } else if (unlikely(wf->smp[2].v == wf->smp[1].v) && delta_t > wf->len / 2) { |
| 91 | + wf->smp[2].v = v; |
| 92 | + wf->smp[2].t = t; |
| 93 | + } |
| 94 | + |
| 95 | + return wf->smp[0].v; |
| 96 | +} |
| 97 | + |
| 98 | +/* Return <wf> windowed filter best maximum estimation. */ |
| 99 | +static inline uint64_t wf_get_max(struct wf *wf) |
| 100 | +{ |
| 101 | + return wf->smp[0].v; |
| 102 | +} |
| 103 | + |
| 104 | +#endif /* _HAPROXY_WINDOW_FILTER_H */ |
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