Flaws Validation of Maze Mobility Model using Spatial-temporal Synthetic Mobility Metrics

Nisrine Ibadah, K. Minaoui, M. Rziza, M. Oumsis, C. Benavente-Peces
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Abstract

Mobility modeling represents a critical task in mobile wireless networks to improve the overall throughput. This paper evaluates relevant spatial-temporal stochastic properties of the most frequently used synthetic mobility models compared to a new efficient mobility model named Maze Mobility Model (Maze MM). It imitates a real-life movement according to diverse mobility features, as spatial and temporal dependencies with also geographic restrictions. To demonstrate the efficiency of this new model, various metrics were validated such as; the speed decay problem, the density wave phenomenon, the spatial node distribution, the average neighbor percentage, and mobile neighbors range. Each mobility pattern may bear from diverse mobility flaws, as shown by network simulations. So, numerous metrics are employed to describe mobility features. The current research aims to deeply understand mobility features of Maze MM with the aim to deduce a definite judgment of each mobility metric, given that further this fact affects the whole network performances. The validation results are discussed to remark the effectiveness and robustness of Maze MM according to the validated mobility metrics.
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基于时空综合迁移度量的迷宫迁移模型缺陷验证
在移动无线网络中,移动性建模是提高整体吞吐量的一项关键任务。本文将最常用的综合迁移模型的时空随机特性与一种新的高效迁移模型迷宫迁移模型(Maze MM)进行了比较。它根据不同的移动特征模仿现实生活中的运动,作为空间和时间的依赖关系,也有地理限制。为了证明这种新模型的有效性,验证了各种指标,例如;速度衰减问题,密度波现象,空间节点分布,平均邻居百分比,移动邻居范围。网络模拟表明,每种迁移模式都可能承受不同的迁移缺陷。因此,许多指标被用来描述移动性特性。本研究旨在深入了解Maze MM的移动性特征,并推导出对每个移动性指标的明确判断,因为这一事实会进一步影响整个网络的性能。对验证结果进行了讨论,根据验证的迁移率指标评价了Maze MM的有效性和鲁棒性。
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