Comparing the impact of mobile nodes arrival patterns in mobile ad hoc networks using poisson and pareto models

Mobile Ad hoc Networks (MANETs) are dynamic networks populated by mobile stations, or mobile nodes (MNs). Mobility model is a hot topic in many areas, for example, protocol evaluation, network performance analysis and so on.How to simulate MNs mobility is the problem we should consider if we want to build an accurate mobility model. When new nodes can join and other nodes can leave the network and therefore the topology is dynamic.Specifically, Mobile Ad hoc Networks consist of a collection of nodes randomly placed in a line (not necessarily straight). Mobile Ad hoc Networks do appear in many real-world network applications such as a vehicular Mobile Ad hoc Networks built along a highway in a city environment or people in a particular location. Mobile Nodes in Mobile Ad hoc Networks are usually laptops, Personal Digital Assistants or mobile phones. This paper presents comparative results that have been carried out via Matrix lab software simulation. The study investigates the impact of mobility predictive models on mobile nodes parameters such as, the arrival rate and the size of mobile nodes in a given area using Pareto and Poisson distributions. The results have indicated that mobile nodes arrival rates may have influence on Mobile Nodes population (as a larger number) in a location. The Pareto distribution is more reflective of the modeling mobility for Mobile Ad hoc Networks than the Poisson distribution.