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Comparing the Impact of Mobile Nodes Arrival Patterns in Manets using Poisson and Pareto Models

机译:使用泊松和帕累托模型比较马奈市移动节点到达模式的影响

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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, 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. This paper presents comparative results that have been carried out via Matlab 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 MNs population (as a larger number) in a location. The Pareto distribution is more reflective of the modeling mobility for MANETs than the Poisson distribution.
机译:移动自组织网络(MANET)是由移动站或移动节点(MN)填充的动态网络。移动性模型是协议评估,网络性能分析等许多领域的热门话题。如何模拟MN的移动性是我们要建立准确的移动性模型时应考虑的问题。当新节点可以加入而其他节点可以离开网络时,拓扑便是动态的。具体地说,MANET由随机排成一条线(不一定是直线)的一组节点组成。 MANET确实出现在许多现实世界的网络应用程序中,例如在城市环境中沿着高速公路或特定位置的人们建造的车载MANET。 MANET中的MN通常是笔记本电脑,PDA或移动电话。本文介绍了通过Matlab软件仿真进行的比较结果。这项研究使用Pareto和Poisson分布调查了移动性预测模型对移动节点参数(如给定区域中移动节点的到达率和大小)的影响。结果表明,移动节点的到达速率可能会影响某个位置中的MN数量(以更大数量计)。与Poisson分布相比,Pareto分布更能反映MANET的建模移动性。

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