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/*
This file is part of GNUnet
Copyright (C) 2013 GNUnet e.V.
GNUnet is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published
by the Free Software Foundation; either version 3, or (at your
option) any later version.
GNUnet is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
General Public License for more details.
You should have received a copy of the GNU General Public License
along with GNUnet; see the file COPYING. If not, write to the
Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor,
Boston, MA 02110-1301, USA.
*/
/**
* @file set/ibf_sim.c
* @brief implementation of simulation for invertible bloom filter
* @author Florian Dold
*
* This code was used for some internal experiments, it is not
* build or shipped as part of the GNUnet system.
*/
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#define MAX_IBF_DECODE 16
/* report average over how many rounds? */
#define ROUNDS 100000
/* enable one of the three below */
// simple fix
#define FIX1 0
// possibly slightly better fix for large IBF_DECODE values
#define FIX2 1
// SIGCOMM algorithm
#define STRATA 0
// print each value?
#define VERBOSE 0
// avoid assembly? (ASM is about 50% faster)
#define SLOW 0
int
main(int argc, char **argv)
{
unsigned int round;
unsigned int buckets[31]; // max is 2^31 as 'random' returns only between 0 and 2^31
unsigned int i;
int j;
unsigned int r;
unsigned int ret;
unsigned long long total;
unsigned int want;
double predict;
srandom (time (NULL));
total = 0;
want = atoi (argv[1]);
for (round=0;round<ROUNDS;round++)
{
memset (buckets, 0, sizeof (buckets));
for (i=0;i<want;i++)
{
/* FIXME: might want to use 'better' PRNG to avoid
PRNG-induced biases */
r = random ();
if (0 == r)
continue;
#if SLOW
for (j=0;(j < 31) && (0 == (r & (1 << j)));j++) ;
#else
/* use assembly / gcc */
j = __builtin_ffs (r) - 1;
#endif
buckets[j]++;
}
ret = 0;
predict = 0.0;
for (j=31;j >= 0; j--)
{
#if FIX1
/* improved algorithm, for 1000 elements with IBF-DECODE 8, I
get 990/1000 elements on average over 1 million runs; key
idea being to stop short of the 'last' possible IBF as
otherwise a "lowball" per-chance would unduely influence the
result */
if ( (j > 0) &&
(buckets[j - 1] > MAX_IBF_DECODE) )
{
ret *= (1 << (j + 1));
break;
}
#endif
#if FIX2
/* another improvement: don't just always cut off the last one,
but rather try to predict based on all previous values where
that "last" one is; additional prediction can only really
work if MAX_IBF_DECODE is sufficiently high */
if ( (j > 0) &&
( (buckets[j - 1] > MAX_IBF_DECODE) ||
(predict > MAX_IBF_DECODE) ) )
{
ret *= (1 << (j + 1));
break;
}
#endif
#if STRATA
/* original algorithm, for 1000 elements with IBF-DECODE 8,
I get 920/1000 elements on average over 1 million runs */
if (buckets[j] > MAX_IBF_DECODE)
{
ret *= (1 << (j+1));
break;
}
#endif
ret += buckets[j];
predict = (buckets[j] + 2.0 * predict) / 2.0;
}
#if VERBOSE
fprintf (stderr, "%u ", ret);
#endif
total += ret;
}
fprintf (stderr, "\n");
fprintf (stdout, "average %llu\n", total / ROUNDS);
return 0;
}
/* TODO: should calculate stddev of the results to also be able to
say something about the stability of the results, outside of
large-scale averages -- gaining 8% precision at the expense of
50% additional variance might not be worth it... */
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