Statistics

The statistics module includes some useful features to ease data collection from experiments. More...

Collaboration diagram for Statistics:

Modules
	Data Aggregators
	Data aggregators are classes used to collect data and produce output specialized for various purpose, e.g., Gnuplot, file output, etc.
	Data Output
	Classes in Data Output group are used to collect and prepare and output data for subsequent output in a specific format, e.g., Omnet++, SQLite, etc.
	Gnuplot
	Classes in Gnuplot group are used to collect and prepare and output data for subsequent processing by Gnuplot.
	Probes
	Probes are used to probe an underlying ns3 TraceSource exporting its value.
	Statistics module tests

Classes
class	ns3::Average< T >
	Simple average, min, max and std. More...
class	ns3::CounterCalculator< T >
	Template class CounterCalculator. More...
class	ns3::DataCalculator
	Calculates data during a simulation. More...
class	ns3::DelayJitterEstimation
	Quick and dirty delay and jitter estimation, implementing the jitter algorithm originally from RFC 1889 (RTP), and unchanged in RFC 3550 More...
class	ns3::FileHelper
	Helper class used to put data values into a file. More...
class	ns3::MinMaxAvgTotalCalculator< T >
	Template class MinMaxAvgTotalCalculator. More...
class	ns3::PacketCounterCalculator
	A stat for counting packets. More...
class	ns3::PacketSizeMinMaxAvgTotalCalculator
	A stat for collecting packet size statistics: min, max and average. More...
class	ns3::SQLiteOutput
	A C++ interface towards an SQLITE database. More...
class	ns3::StatisticalSummary
	Abstract class for calculating statistical data. More...
class	ns3::TimeMinMaxAvgTotalCalculator
	Unfortunately, templating the base MinMaxAvgTotalCalculator to operate over Time values isn't straightforward. More...

Detailed Description

The statistics module includes some useful features to ease data collection from experiments.

In particular the following features are included:

• The core framework and two basic data collectors: A counter, and a min/max/avg/total observer.
• Extensions of those to easily work with times and packets.
• Plaintext output formatted for OMNet++.
• Database output using SQLite, a standalone, lightweight, high performance SQL engine.
• Mandatory and open ended metadata for describing and working with runs.

See the manual for a complete documentation.