Introducing Geographic Restrictions to the SLAW Human Mobility Model
Introducing Geographic Restrictions to the SLAW Human Mobility Model
复制标题
将地理限制引入 SLAW 人员流动模型
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
N. Aschenbruck
中科院分区：
文献类型：
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作者：
Matthias Schwamborn;N. Aschenbruck
在其他统计特征中，对来自不同户外场景的细粒度GPS轨迹的分析表明，人类移动在统计上类似于勒维步行，并导致了自相似最小动作步行（SLAW）移动模型的设计。得出的结论是，人员流动是无尺度的，这一特点是不变的，无论任何地理限制。这些限制被认为过于具体，在SLAW中被省略。然而，我们认为，地理限制不应该被认为是一个不必要的细节，但作为一个现实的移动性模型的一个重要特征的模拟性能评估的移动的网络。因此，我们以地图的形式为SLAW引入地理限制。我们的扩展模型（称为MSLAW）的评估表明，引入的限制有显着的影响，机会网络相关的几个性能指标。
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.