Introducing Geographic Restrictions to the SLAW Human Mobility Model

Matthias Schwamborn, N. Aschenbruck
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引用次数: 19

Abstract

Among other statistical features, the analysis of fine-grained GPS traces from different outdoor scenarios has shown that human mobility statistically resembles Lévy Walks and led to the design of the Self-similar Least-Action Walk (SLAW) mobility model. It was concluded that human mobility is scale-free and that this feature is invariant irrespective of any geographic constraints. These constraints were considered too scenario-specific and were omitted in SLAW. However, we argue that geographic constraints should not be considered as an unnecessary detail, but as an important feature of a realistic mobility model for the simulative performance evaluation of mobile networks. Therefore, we introduce geographic restrictions to SLAW in the form of maps. Our evaluation of the extended model (called MSLAW) shows that the introduced restrictions have a significant impact on several performance metrics relevant for opportunistic networks.
引入地理限制的SLAW人类流动模型
在其他统计特征中,对来自不同户外场景的细粒度GPS痕迹的分析表明,人类的移动性在统计上与lsamvy Walks相似,并导致了自相似最小行动步行(SLAW)移动性模型的设计。得出的结论是,人类的流动性是无标度的,这一特征是不变的,无论任何地理限制。这些约束被认为过于特定于场景,因此在SLAW中被省略了。然而,我们认为地理约束不应该被视为一个不必要的细节,而是作为一个现实的移动模型的重要特征,用于模拟移动网络的性能评估。因此,我们以地图的形式对SLAW进行地理限制。我们对扩展模型(称为MSLAW)的评估表明,引入的限制对机会网络相关的几个性能指标有重大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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