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package Smokeping::matchers::Median;
=head1 NAME
Smokeping::matchers::Median - Find persistant changes in latency
=head1 OVERVIEW
The idea behind this matcher is to find sustained changes in latency.
The median matcher takes a number of past median latencies. It splits the latencies into
two groups (old and new) and again finds the median for each groups. If the
difference between the two medians is bigger than a certain value, it will
give a match.
=head1 DESCRIPTION
Call the matcher with the following sequence:
type = matcher
pattern = Median(old=>x,new=>y,diff=>z)
This will create a matcher which consumes x+y latency-datapoints, builds the
two medians and the matches if the difference between the median latency is
larger than z seconds.
=head1 COPYRIGHT
Copyright (c) 2004 by OETIKER+PARTNER AG. All rights reserved.
=head1 LICENSE
This program 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 2 of the License, or
(at your option) any later version.
This program 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 this program; if not, write to the Free Software
Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
=head1 AUTHOR
Tobias Oetiker <tobi@oetiker.ch>
=cut
use strict;
use base qw(Smokeping::matchers::base);
use vars qw($VERSION);
$VERSION = 1.0;
use Carp;
sub new(@)
{
my $class = shift;
my $rules = {
old=>'\d+',
new=>'\d+',
diff=>'\d+(\.\d+)?' };
my $self = $class->SUPER::new($rules,@_);
return $self;
}
# how many values does the matcher need to do it's magic
sub Length($)
{
my $self = shift;
return $self->{param}{old} + $self->{param}{new};
}
sub Desc ($) {
croak "Find changes in median latency";
}
sub Test($$)
{ my $self = shift;
my $data = shift; # @{$data->{rtt}} and @{$data->{loss}}
my $ac = $self->{param}{old};
my $bc = $self->{param}{new};
my $cc = $ac +$bc;
my $count = scalar @{$data->{rtt}};
$cc = $count if $count < $cc;
$bc = $count if $count < $bc;
my $oldm = robust_median(@{$data->{rtt}}[-$cc..-$bc-1]);
my $newm = robust_median(@{$data->{rtt}}[-$bc..-1]);
return abs($oldm-$newm) > $self->{param}{diff};
}
sub robust_median(@){
my @numbers = sort {$a <=> $b} grep { defined $_ and $_ =~ /\d/ } @_;
my $count = $#numbers;
return 0 if $count < 0;
return ($count / 2 == int($count/2)) ? $numbers[$count/2] : ($numbers[$count/2+0.5] + $numbers[$count/2-0.5])/2;
}
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