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Modeling and simulation of an improved random direction mobility model for wireless networks using colored Petri nets

机译:改进的有色Petri网用于无线网络的随机方向移动性模型的建模和仿真

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Wireless networks have received increased attention from researchers due to their extensive set of applications and ubiquitous communication facility. The underlying mobility model plays a key role in mobility management, which is a prominent communication means in delivering services to mobile users accurately. Random direction is a synthetic mobility model that is widely used in simulators, while simulation is universally considered the most effective method for the design and analysis of the characteristics of mobility models. However, simulation is limited in its capabilities and it may generate unrealistic, error-prone results and consume more time. Further, the random direction mobility model produces unrealistic movement patterns due to a sharp turn problem and it forces the mobile host to travel to the edge of the terrain. To alleviate the issues of the random direction mobility model, this paper presents a colored Petri net (CPN)-based formal approach as an improved direction mobility model. Further, the proposed algorithm to tackle the sharp turn problem is implemented by using the CPN formalism. The formal semantics of the CPN allow a graphical, intuitive approach to design, simulate, execute, and validate the model.
机译:无线网络由于其广泛的应用范围和无处不在的通信设施而受到越来越多研究人员的关注。基本的移动性模型在移动性管理中起着关键作用,移动性管理是在向移动用户准确交付服务中的一种重要通信手段。随机方向是一种综合的流动性模型,已在模拟器中广泛使用,而普遍认为模拟是设计和分析流动性模型特征的最有效方法。但是,仿真的功能有限,可能会产生不切实际,容易出错的结果,并且会花费更多时间。此外,随机方向移动性模型由于急转弯问题而产生了不切实际的运动模式,并迫使移动主机移动到地形的边缘。为了缓解随机方向迁移模型的问题,本文提出了一种基于彩色Petri网(CPN)的形式化方法,作为一种改进的方向迁移模型。此外,通过使用CPN形式主义实现了解决急转弯问题的算法。 CPN的形式语义允许使用图形化,直观的方法来设计,模拟,执行和验证模型。

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