Comparing the Impact of Mobile Nodes Arrival Patterns in Manets 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, networkperformance analysis and so on.How to simulate MNs mobility is the problem we should consider if wewant to build an accurate mobility model. When new nodes can join and other nodes can leave the networkand therefore the topology is dynamic.Specifically, MANETs consist of a collection of nodes randomlyplaced in a line (not necessarily straight). MANETs do appear in many real-world network applicationssuch as a vehicular MANETs built along a highway in a city environment or people in a particularlocation. MNs in MANETs are usually laptops, PDAs or mobile phones.This paper presents comparative results that have been carried out via Matlab software simulation. Thestudy investigates the impact of mobility predictive models on mobile nodes’ parameters such as, thearrival rate and the size of mobile nodes in a given area using Pareto and Poisson distributions. Theresults have indicated that mobile nodes’ arrival rates may have influence on MNs population (as a largernumber) in a location. The Pareto distribution is more reflective of the modeling mobility for MANETsthan the Poisson distribution