Comparative Study of Predictive Mobility Models for Manets by Simulation

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Date
2012
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Abstract
Mobile Ad hoc Networks (MANETs) are dynamic networks populated by mobile stations or mobile nodes (MNs). Specifically, MANETs consist of a collection of nodes randomly placed in a line (not necessarily straight). MANETs do appear in many real-world network applications such as a vehicular MANETs built along a highway in a city environment or people in a particular location. MNs in MANETs are usually laptops, PDAs or mobile phones. These devices may use Bluetooth and/or IEEE 802.11 (Wi-Fi) network interfaces and communicate in a decentralized manner. Mobility is a key feature of MANETs. Each node may work as a router and the network can dynamically change with time; when new nodes can join, and other nodes can leave the network. In this thesis, comparative results of the Queueing Mobility Model and mobility models such as random walk/Brownian model have been carried out via Matlab software simulation. The study investigates the impact of mobility prediction models on mobile nodes‟ parameters such as the speed, the arrival rate and the size of mobile nodes in a given area. The results have indicated that mobile nodes‟ arrival rates may have influence on MNs population (as a larger number) in a location. An initial position of nodes has appeared to have a significant effect on their movement pattern (trajectory). The Pareto distribution is more reflective of the modeling mobility for MANETs than the Poisson distribution. Keywords: Mobility Models, MANETs, Pareto, Simulation, Poisson Distribution, Arrival Patterns.
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A Thesis submitted to the Department of Telecommunications Engineering, Kwame Nkrumah University of Science and Technology, in partial fulfilment of the requirement for the degree of Master of Science.
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