Mobility Models

Mininet-WiFi supports the following mobility models:

• RandomWalk
• TruncatedLevyWalk
• RandomDirection
• RandomWayPoint
• GaussMarkov
• ReferencePoint
• TimeVariantCommunity

How to configure mobility models?

The mobility models can be configured with net.setMobilityModel(). For example:

net.setMobilityModel(time=0, model='RandomDirection',
                     max_x=100, max_y=100, seed=20)

time: time (in seconds) in which the mobility is started
model: mobility model
max_x: maximum x value
min_x: minimum x value
seed: defines a starting value for a pseudo random sequence

In addition, you may want to consider some parameters that be can be used when you add some node:

Random Walk

sta1 = net.addStation( ..., min_x=10, max_x=20, min_y=10, max_y=20, constantDistance=1, constantVelocity=1 )

min_x = Minimum X position # default=0
max_x = Maximum X position # default=100
min_y = Minimum Y position # default=0
max_y = Maximum Y position # default=100
constantDistance = the value for the constant distance traveled in each step. Default is 1.0.
constantVelocity = the value for the constant node velocity. Default is 1.0

Random Direction

sta1 = net.addStation( ..., min_x=10, max_x=20, min_y=10, max_y=20, min_v=1, max_v=2 )

min_x = Minimum X position # default=0
max_x = Maximum X position # default=100
min_y = Minimum Y position # default=0
max_y = Maximum Y position # default=100
min_v = Minimum value for node velocity
max_v = Maximum value for node velocity

Random Way Point

sta1 = net.addStation( ..., min_x=10, max_x=20, min_y=10, max_y=20, min_v=1, max_v=2, min_wt=0, max_wt=100 )

min_x = Minimum X position # default=0
max_x = Maximum X position # default=100
min_y = Minimum Y position # default=0
max_y = Maximum Y position # default=100
min_v = Minimum value for node velocity # default=5
max_v = Maximum value for node velocity # default=5
min_wt = Minimum wait time # default=0
max_wt = Maximum wait time # default=100

Gauss Markov

sta1 = net.addStation( ..., min_x=10, max_x=20, min_y=10, max_y=20 )

min_x = Minimum X position # default=0
max_x = Maximum X position # default=100
min_y = Minimum Y position # default=0
max_y = Maximum Y position # default=100

Reference Point Group

sta1 = net.addStation( ..., min_x=10, max_x=20, min_y=10, max_y=20 )

min_x = Minimum X position # default=0
max_x = Maximum X position # default=100
min_y = Minimum Y position # default=0
max_y = Maximum Y position # default=100

net.setMobilityModel(time=0, model='ReferencePoint', n_groups=2,
                     max_x=100, max_y=100, seed=20)

Custom Mobility

You can also define custom mobility. To do so, you may want to refer to examples/mobility.py and examples/replaying/replayingMobility.py for more information.

Handover association mechanisms

Two mechanisms can be considered:

• Least Loaded First (llf)
• Strongest Signal First (ssf)

You can use them when the mobility is started. For example:

net.startMobility(time=0, ac_method='ssf')
...
...
net.stopMobility(time=10)

or

net.setMobilityModel(... ac_method='ssf')

However, if you want to work with a seamless handover you may want to refer to bgscan (see examples/handover_bgscan.py)

In scenarios where there is no mobility you can enable ac_method within Mininet_wifi(). For example:

Mininet_wifi(... ac_method='ssf')