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A fuzzy logic controlled mobility model based on simulated traffics' characteristics in MANET

机译:一种基于模拟交通特征的模糊逻辑控制移动模型

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In this paper, we investigate the self-similarity characteristic of MANET(Mobile Ad-hoc NETworks) traffics through simulations and then construct a fuzzy logic controlled mobility model according to the traffic feature to optimize the network performance. First, based on the generated traffics using OPNET, the self-similarity of MANET traffics has been verified with a qualitative analysis. Then, by exploring the relation between the self-similarity indicator, i.e., Hurst and some network performance metrics, such as Packets Delivery Ratio(PDR), Average Transmission Delay(ATD) and nodal Average Moving Speed(AMS), a fuzzy logic controller is designed to make the mobility model adaptively work in order to output satisfied performance. By online estimating the self-similarity of incoming traffics using R/S analysis, the Packet Size(PS) and AMS of each vehicle could be intelligently adjusted to maximize the PDR and minimize the experienced ATD. Numerical results indicate that our proposed mobility model, compared to the classic mobility model RWP(Random WayPoint), has a better performance in terms of PDR and ATD.
机译:在本文中,我们调查MANET的自相似特性(移动ad-hoc网络)通过模拟流量,然后根据流量特性来优化网络性能构造一个模糊逻辑控制的移动性模型。首先,基于使用OPNET的产生的业务,MANET流量的自相似性已经验证了定性分析。然后,通过探索的自相似性指示符之间的关系,即,赫斯特和一些网络性能度量,诸如数据包投递率(PDR),平均传输延时(ATD)和节点平均移动速度(AMS)中,模糊逻辑控制器旨在使以满足输出性能的移动性模型自适应工作。通过在线估计使用R / S分析传入的业务流的自相似性,各车辆的分组大小(PS)和AMS可以智能地调整以最大化PDR和尽量减少经验ATD。计算结果表明,我们提出的移动模型,相比于传统移动模型RWP(随机航点),在人民民主共和国和ATD方面有更好的表现。

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