Wireless networks simulation.
Wireless networks simulation
Performance evaluation of a protocol for ad hoc networks is usually performed by simulating the wireless network. Simulation provides the researcher with a number of significant benefits, including repeatable scenarios, isolation of parameters and exploration of a variety of metrics.
In particular, A Wireless Network simulation MUST model:
Mobile Nodes’ characteristics such as: transmission range, limited buffer capacity, battery power limitations, signals radio propagation ect.
Communication traffic model (what kind of data flow is there?)
Mobility model (movements of the users i.e. devices)
a few others
Trace vs. Synthetic mobility models (1)
Trace vs. Synthetic mobility models (2)
Synthetic mobility models classification
Random Walk (1)
1) Nodes start moving at t=0. Choosing a DURATION implies that all the nodes change directions at the same time and travel for different distances. In contrast, choosing a DISTANCE implies same distances but different duration.
2) The pattern is memory-less i.e. current speed and direction do not depend upon the previous ones. Therefore, there will be sharp and sudden turns.
3) Short tm or d lead the nodes to move around their current location. Unless it is necessary to study a semi-static network, they MUST be chosen large.
Random Walk (2)
Example of a travelling pattern of a mobile node using the 2D Random Walk MM
Surface size 300 x 600 m, tm = 60s
Random Waypoint (1)
Random Waypoint (2)
Example of a travelling pattern of a mobile node using the Random Waypoint MM
Surface size 300 x 600 m
Random Direction (1)
Random Direction (2)
Example of a travelling pattern of a mobile node using the Random Direction MM
Surface size 300 x 600 m
Gauss - Markov (3)
Example of a travelling pattern of a mobile node using the Gauss Markov MM
Surface size 300 x 600 m
Probabilistic Random WALK
The probabilities to switch from a state to another are:
Each non zero probability is a transition in the state chart.
A possible implementation is shown in Chiang  (speed const.)
City mobility model
it represents a section of a city where an ad-hoc network operates . It models factors as:
A street network
A set of buildings
Destination points ( where nodes randomly start from and hear for )
it is a group MM, Suitable for representing soldiers marching:
Initially a reference point is chosen and assigned to each MNs. The peculiarity is to choose points on a line (culumn)
Nodes are subsequently allowed to move around their reference point according to an Entity MM
Reference points change:
New_ref_point = Old_ref_point + advance_vector
where: advance_vector = (x,y)
When this happens, MNs move toward their ref. Point to start roaming around.
Nomadic community MM
it is a group MM, Suitable for representing Nomadic Movements (a class of students visiting a museum ect.):
Initially a reference point is chosen and SHARED between all the MNs.
Nodes are subsequently allowed to move around it according to an Entity MM
the reference point randomly changes causing the nodes to firstly reach it and then to roam around it
Column vs. Nomadic community MM
A set of MNs want to catch a running away MN.
NewPosition = OldPosition + Dist + RandomDist
Dist is a vector (x,y) whose components are chosen in [MinDX, MaxDX] and [MinDY, MaxDY].
RandomDist is a vector (x,y) obtained via Entity MM.
A set of MNs want to move in group. The group has a logical center which moves.
Each MN is assigned a moving reference point. Nodes randomly move around it.
Two kinds of motion:
i) Group Motion is represented by a vector GM
ii) nodes Random Motion is represented by RM
The group logical center is assigned a new position at regular intervals.
Subsequently the RPs locations are updated accordingly. Finally MNs
locations are computed based on GM and RM
Designed to represent avalanche rescue. (humans & dogs)
The MNs movements are characterized by the group logical center’s motion.
Many particular possible implementations. For instance:
1) Nomadic Community MM (no separation between RPs)
2) Column MM (by disposing the RPs in a column)
3) Pursue MM (no separation between RPs)
i) # nodes 50
ii) Routing Prot. DSR
iii) Sim. Time 1000 sec
iv) Random initial locations
v) Sim. Results are shown by averaging 10 trials
i) 20 UDP pairs S/R (CBR)
iii) pkt size 64 bytes each
* RPGM Inter+Intra sends:
-1pkt/2sec Inter (20 pairs distributed in 16 groups)
i) # control packets / Pck_received
ii) # control byte transmitted / Pck_received
it includes control bytes in both control and data packets.
 Tracy Camp, Jeff Boleng, Vanessa Davies. A survey of mobility for ad hoc network research. Dept. of Math. and Computer Sciences Colorado School of Mines, September 2002. V. Tolety. Load reduction in ad hoc networks using mobile servers. Master’s thesis, Colorado School of Mines, 1999.  C. Chiang Wireless Network Multicasting., Phd. Thesis, University of California, Los Angeles 1998. F. Bai, N. Sadagopan, A. Helmy, A framework to systematically the impact of mobility on performance of routing protocols for AdHoc networks. IEEE Infocom 2003.
Write to: Stefano Marinoni [email protected]: T-B235 lab for theoretical CS