Gugrajah_Yuvaan_ Ramesh_2003.pdf
Gugrajah_Yuvaan_ Ramesh_2003.pdf
Gugrajah_Yuvaan_ Ramesh_2003.pdf
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SimuLation ofa Load BaLancing Routing ProtocoL Chapter 3<br />
result is an aggregate effective movement that can be modelled by a suitable random<br />
process.<br />
The mobility model implemented in the simulator is the random waypoint model<br />
[Broch98]. The random waypoint model [Broch98] has been used by the MANET<br />
workgroup of the IETF and was fust introduced by the eMU group for the ns2<br />
network simulator.<br />
In the Random Waypoint Model the nodes are initially assigned random positions<br />
and then select a randomly distributed destination and a random speed between<br />
predefined limits, and travel to the destination at that speed. On arrival the node<br />
waits for a "pause time" before repeating the procedure to move to a new destination.<br />
[DaviesOO] found that the network is more stable in terms of link breakages over<br />
time in simuJations with fast mobile nodes and long pause times as opposed to slow<br />
mobile nodes and short pause times. Figure 3-5 is a flowchart of the implementation<br />
of the Random Waypoint Model for a mobile node in the simulator. For the<br />
simulations the values for x_max and y_max were both 1000 m and v_max was 20<br />
rn/s. The pause_time used was 0, 25s, 50s and 150s for different simulation runs. By<br />
varying the pause times, different mobility scenarios were simulated.<br />
[RoyerOl] modified the Random Waypoint Mobility model after it was found that<br />
density waves were created in the average number of neighbours during a simulation.<br />
The average number of neighbours seen at a given node periodically increases and<br />
decreases as the simulation progresses, where the frequency of the change is relative<br />
to the speed of the nodes. The density waves are as a result of nodes repeatedly<br />
moving towards the centre or passing through the centre of the designated network<br />
area since statistically the nodes choose a new position from where there are most<br />
positions to choose.<br />
The modification resulted in the Random Direction Model to alleviate this behaviour<br />
and promote a semi-constant number of neighbours during the simulation. Nodes are<br />
requested to choose a direction and speed, instead of destination, until a boundary is<br />
reached. The nodes then wait for a certain "pause time" before choosing another<br />
3-13
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