DES statistics:

                           When once all the above settings are done, the system is prepared to collect the statistical data and for the work space must be selected and then give right click and must select the “select Individual DES statistics” from the options given, and then a new window gets open. In general there are three types of statistics and they are node statistics, global statistics and link statistics as discussed in the design chapter of this document.

The determination of the entire network performance is based on the global statistics application whereas the application of node statistics determines the performance of the individual mobile nodes. The evaluation of the individual mobile node performance is done based on conditions invoked in this phenomenon. As the main aim of this project is to compare the performance of TCP against CBR traffic in this scenario AODV routing protocol is used and few performance metrics are used for estimating the performances and for the comparison and they are the throughput and delay.

The LHS and wireless LAN options are expanded for the node statistics to select the attributes of throughput and delay. The collection mode can be changed by verifying the advanced options. All this explained using the screenshots given in the appendix. The applied DES statistics are as follows:

 “Wireless LAN: Control Traffic sent and Traffic received (bytes/sec)

Wireless LAN: Delay (sec), throughput (bit/sec)”                                              

                           Therefore using these metrics the performance of the traffics are estimated and further comparisons are made throughout the MANET. When all the required metrics are defined then the scenario is set ready for the simulation and the next section explains the simulation procedure.

Running the Simulation:

                        The next step after setting all the required setups like statistical settings and configuration setting is running the simulation of the scenario. This application has selected 200 mobile nodes to do the simulation as discussed earlier and 2 minutes is taken as the simulation time to run the simulation and the appendix section is attached with screen shots of the simulation to provide better understanding. Few parameters are required for this scenario and they are as follows:

  • 2 minutes is taken as simulation duration
  • 128 is taken as speed of simulation
  • 200 as the statistical value
  • 5000000 events as the update intervals 

                         When once all these parameters are selected then the simulation of the scenario is set ready for running and the Run button is selected for starting the simulation procedure. If the simulation of scenario is executed perfectly then the results are obtained and they are explained in the next chapter that is the results and analysis.

Simulation of Scenario 2:

                       Once the simulation of scenario 1 is completed, as a next step the process for the simulation of scenario 2 gets started. In order to create the second scenario the tool bar of the work station is used by selecting the scenario menu and then by choosing the “duplicate scenario” option. Then the scenario 2 is created, this scenario is similar to scenario 1 but the only difference in both is the generated traffic and the application used. The configuration of the application must be done by modifying the parameters of the application just by selecting the edit option and the values modified are as follows:

  • Number of rows is taken as 1
  • CBR is taken as the traffic
  • Low quality voice application is selected as the description
  • Voice destination is selected as the name of symbolic server. 

                              Once the application settings are changed the project is saved and then as the next step the profile configuration settings are made by selecting the edit profile option. And the values required for editing the profile attributes are indicated below:

  • CBR is taken as the name of the profile
  • Number of rows for application is taken as 1
  • CBR as the name of the application
  • Offset start time is selected as constant that is 5 sec
  • Duration is set as profile ending
  • Serial is set as mode of operation
  • Uniform (100,110) is selected as the start time
  • Repeatability is set as once at start duration
  • End of simulation is set for the duration

                            All the attributes given above are same to the scenario 1 but the application used is different. Based on the application setting and profile setting done, the mobile setting and server settings are also edited. Then the deployment procedure is similar to that in the scenario 1. And the statistics are also similar to the scenario 1 as given: 

UDP: “Traffic sent (bytes/sec) and Traffic received (bytes/sec)”

Wireless LAN: Control Traffic sent and Traffic received (bytes/sec)

Wireless LAN: “Delay (seconds) and Throughput (bits/sec)”.

Simulation of other scenarios:

                     As it is already discussed above there are eight scenarios in this simulation project and the main aim of all these scenarios is to estimate the performance of TCP traffic over CBR traffic using different routing protocols. The above two scenarios, scenario 1 and scenario 2 are simulated for generating the TCP and CBR traffics respectively by using the AODV routing protocol. Similarly in case of the scenario 3 and scenario 4 all the settings and configurations are similar to scenario 1 and scenario 2 for the generation of TCP and CBR traffics respectively but the only difference is using the DSR routing protocol. The scenario 5 and scenario 6 uses the OLSR routing protocol for the generation of TCP and CBR traffics across the MANETs. Similarly the scenario 7 and scenario 8 are also simulated for the generation of TCP and CBR traffics across the MANETs using the TORA routing protocol. The results of all the scenarios are obtained and used for the individual estimation of traffic performances and then used for the comparison of the performances of the traffics in terms of few performance metrics. 

This paper is written and submitted by Sujana Priya V.