MarkovScheduler

simple module

This module implements a packet scheduler using a Markov process that has as many states as input gates the scheduler has. The input gate for the next packet is determined by the current state of the Markov process.

Inheritance diagram

The following diagram shows inheritance relationships for this type. Unresolved types are missing from the diagram.

Used in compound modules

Name	Type	Description
BurstyPacketProducer	compound module	This module mixes two different packet sources to generate bursty traffic.

Extends

Name	Type	Description
PacketSchedulerBase	simple module	This is a base module for various packet scheduler modules. Derived modules must implement a single packet scheduler function which determines the index of the input gate for the popped packet.

Parameters

Name	Type	Default value	Description
displayStringTextFormat	string	"classified %p pk (%l)\ncurrent state: %s"	determines the text that is written on top of the submodule
initialState	int	0	the start state of the Markov process
transitionProbabilities	string		the transition matrix (N x N) of the Markov process, specified as a list of probabilities
waitIntervals	string		the amount of time the Markov process stays in a given state, a list of intervals (N) indexed by the state

Properties

Name	Value	Description
display	i=block/join
class	MarkovScheduler

Gates

Name	Direction	Size	Description
in [ ]	input
out	output

Signals

Name	Type	Unit
packetPopped	inet::Packet

Statistics

Name	Title	Source	Record	Unit	Interpolation Mode
packetPopped	packets popped		count, sum(packetBytes), vector(packetBytes)		none

Source code

//
// This module implements a packet scheduler using a Markov process that has
// as many states as input gates the scheduler has. The input gate for the next
// packet is determined by the current state of the Markov process.
//
simple MarkovScheduler extends PacketSchedulerBase like IPacketScheduler
{
    parameters:
        displayStringTextFormat = default("classified %p pk (%l)\ncurrent state: %s");
        int initialState = default(0); // the start state of the Markov process
        string transitionProbabilities; // the transition matrix (N x N) of the Markov process, specified as a list of probabilities
        string waitIntervals; // the amount of time the Markov process stays in a given state, a list of intervals (N) indexed by the state
        @class(MarkovScheduler);
}

File: src/inet/queueing/scheduler/MarkovScheduler.ned