Helpdesk Queue Analyser PDQ::Perl
June 23, 2014 § 1 Comment
Below is a Perl script using the PDQ Perl module to analyser the performance of two helpdesk and predict their behaviour should their queues be merged.
A more complete discussion of the motivations for this and conclusions can be found here:
#/usr/bin/perl
use pdq;
use strict;
use warnings;
my $siteAStaff = $ARGV[0];
my $siteAServiceTime = $ARGV[1];
my $siteARate = $ARGV[2];
my $siteBStaff = $ARGV[3];
my $siteBServiceTime = $ARGV[4];
my $siteBRate = $ARGV[5];
#Handle site A
pdq::Init(“Open Network with M/M/N”);
pdq::SetComment(“Simulation of site A mean performance.”);
pdq::CreateOpen(“work”, $siteARate);
pdq::CreateMultiNode( $siteAStaff, “cores”, $pdq::CEN, $pdq::FCFS);
pdq::SetDemand(“cores”, “work”, $siteAServiceTime);
pdq::SetWUnit(“Calls”);
pdq::SetTUnit(“Mins”);
pdq::Solve($pdq::CANON);
my $responseA = substr(pdq::GetResponse($pdq::TRANS, “work”),0, 8);
my $utilA = substr(pdq::GetUtilization(“cores”, “work”, $pdq::TRANS) * 100,0, 4);
#Handle site B
pdq::Init(“Simulation of site B mean performance.”);
pdq::SetComment(“Simulation of 8 core CPU under transactional load.”);
pdq::CreateOpen(“work”, $siteBRate);
pdq::CreateMultiNode( $siteBStaff, “cores”, $pdq::CEN, $pdq::FCFS);
pdq::SetDemand(“cores”, “work”, $siteBServiceTime);
pdq::SetWUnit(“Calls”);
pdq::SetTUnit(“Mins”);
pdq::Solve($pdq::CANON);
my $responseB = substr(pdq::GetResponse($pdq::TRANS, “work”),0, 8);
my $utilB = substr(pdq::GetUtilization(“cores”, “work”, $pdq::TRANS) * 100,0, 4);
#Handle combined site
pdq::Init(“Open Network with M/M/N”);
pdq::SetComment(“Simulation of comined site mean performance.”);
pdq::CreateOpen(“work”, $siteARate + $siteBRate);
pdq::CreateMultiNode( $siteAStaff + $siteBStaff, “cores”, $pdq::CEN, $pdq::FCFS);
pdq::SetDemand(“cores”, “work”, ($siteAStaff * $siteAServiceTime + $siteBStaff * $siteBServiceTime) / ($siteAStaff + $siteBStaff) );
pdq::SetWUnit(“Calls”);
pdq::SetTUnit(“Mins”);
pdq::Solve($pdq::CANON);
my $responseAB = substr(pdq::GetResponse($pdq::TRANS, “work”),0, 8);
my $utilAB = substr(pdq::GetUtilization(“cores”, “work”, $pdq::TRANS) * 100,0, 4);
printf “Site \t| Response \t | utilization\n”;
printf “A \t| %f \t | % 4d\n”, $responseA, $utilA;
printf “B \t| %f \t | % 4d\n”, $responseB, $utilB;
printf “Combined\t| %f \t | % 4d\n”, $responseAB, $utilAB;
Syntax:
perl ./helpdesk_response.pl <siteA call helpdesk staff#> <siteA service time (mins)> <siteA calls per minute> <siteB call helpdesk staff#> <siteB service time (mins)> <siteB calls per minute>
NB: Service time is used here, not response time, so time spent in the queue doesn’t count. Response time is used in the outputted performance.
Example:
perl ./helpdesk_response.pl 4 30 0.08 6 30 .18
Site | Response | utilization
A | 35.382050 | 60
B | 67.006280 | 90
Combined | 34.990830 | 78
Perl PDQ: 8 core response time under load
May 15, 2014 § 1 Comment
The following Perl PDQ1; script was used to generate the response time data for the 8 core example in my https://ascknd.com/2014/05/02/nfs-vs-fibre-cpu-vmware/ post:
#/usr/bin/perl
use pdq;
$cores = $ARGV[0];
$servTime = $ARGV[1];
$max_rate = (1 / $servTime) * $cores;
print “response(secs)\t | util_%\n”;
for ($rate = 0; $rate < $max_rate ; $rate += $max_rate / 5) {
$arrivRate = $rate;
pdq::Init(“Open Network with M/M/N”);
pdq::SetComment(“Simulation of N CPU cores under transactional load.”);
pdq::CreateOpen(“work”, $arrivRate);
pdq::CreateMultiNode( $cores, “cores”, $pdq::CEN, $pdq::FCFS);
pdq::SetDemand(“cores”, “work”, $servTime);
pdq::SetWUnit(“IOS”);
pdq::SetTUnit(“Secs”);
pdq::Solve($pdq::CANON);
$response = substr(pdq::GetResponse($pdq::TRANS, “work”),0, 8);
$util = substr(pdq::GetUtilization(“cores”, “work”, $pdq::TRANS) * 100,0, 4);
printf “$response \t | % 4d\n”, $util;
}
perl ./mm8_response.pl 8 0.000127
response(secs) | util_%
0.000127 | 0
0.000127 | 20
0.000127 | 40
0.000132 | 60
0.000163 | 80
ascknd 