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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, networkperformance analysis and so on.How to simulate MNs mobility is the problem we should consider if wewant to build an accurate mobility model.Whennew nodes canjoinandother 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 usuallylaptops, PDAs or mobile phones.This paper presents comparative results that have been carried out via Matlab software simulation. Thestudyinvestigates 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
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。移动模型是协议评估,网络性能分析等许多领域的热门话题。如果想建立一个精确的移动性模型,就应该考虑这个问题。当新节点可以加入而其他节点可以离开网络时,拓扑是动态的。特别是,MANET由一组随机排列在一条线上的节点组成(不一定是直线)。 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建造的车辆MANET或特定位置的人们。 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软件仿真得出的比较结果。该研究使用帕累托和泊松分布研究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的MN数量(数量较大)。与Poisson分布相比,Pareto分布更能反映MANETs的建模移动性。

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