A New Class of Mobility Models for Ad Hoc Wireless Networks Rahul Amin Advisor: Dr. Carl Baum Clemson University SURE 2006
Brief Overview Background on Random Waypoint Model Description of New Model Observations and Conclusions Future Work
Random Waypoint Model Choose a random point (waypoint) distributed uniformly over some area Choose a random velocity and move from current waypoint to the next using this velocity v1v1 v3v3 v2v
Motivation Random Waypoint Model is too idealistic Nodes can move freely without restrictions Model a more real-world scenario Obstructions in mobility Obstructions in communication
New Model Description Outer circle radius fixed at 1000 m Inner circle represents obstruction and its radius can be varied Obstruction can affect mobility as well as communication Constant velocity model used (10 m/sec) Distribution sampled every 1 sec
New Model Description (contd.) Waypoint is described by Radius (R) and Angle (Θ) R and Θ are independent Generate a Uniform Random Variable in (0,1) interval using Mersenne Twister algorithm
New Model – Boundary Prevention Node smartly predicts if it is going to collide with the obstruction To prevent collision, the waypoint is discarded and a new waypoint is generated
Collision Prediction Calculations
Generated Waypoint Efficiency Efficiency decreases as the radius of obstruction is increased Acceptable efficiency – not going to slow simulation drastically
Steady State Density Peak value shifts right as obstruction radius is increased Close to being spatially uniform
Network Partitions Partition The inability of any one node to be able to connect to any other node for a given distribution Spanning Tree Tree that spans every node in the distribution without forming loops Kruskal’s Minimum Spanning Tree Algorithm used to study network partitions
Network Partitions - Mobility Blocking, No Communication Blocking The maximum hop distance used was ½R = 500 m In this range, lowest Probability of Partition when obstruction radius = 400 m
Network Partitions – Mobility & Communication Blocking The maximum hop distance used was ½R = 500 m Pretty similar characteristics to just mobility blocking
Average Required Power Per Node Maximum hop Distance: 2R No Partitions Assumes perfect knowledge of required power values
Effects of Imperfect Knowledge on Required Power Values Nodes = 30 Update Period: Time before nodes figure out that the best path to minimize power has changed As the update period increases, required power increases
Conclusions Effects of obstructions on Random Waypoint Model were studied A more customizable model presented
Future Work Use Markov velocity model Create multiple obstructions with different radii Change the path metrics for choosing the routes required for minimum power
Acknowledgements Dr. Carl Baum Clemson University SURE Program National Science Foundation ECE faculty and Graduate Students
Questions