基于增强马尔可夫链算法的手机用户移动性预测

Amnir Hadachi, Oleg Batrashev, Artjom Lind, Georg Singer, E. Vainikko
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引用次数: 34

摘要

提出了一种基于增强马尔可夫链算法的手机用户移动性预测方法。手机数据具有高度动态性和少采样性;因此,对用户移动位置的预测提出了一个挑战。我们的增强方法可以概括为应用于马尔可夫链算法的嵌入式规则关联。提议的解决方案对于下一代移动网络来说是令人鼓舞的,它可以用来优化现有的移动网络基础设施、道路交通、跟踪系统和定位。利用现场采集的真实数据对系统进行了验证。
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Cell phone subscribers mobility prediction using enhanced Markov Chain algorithm
This article presents a mobility prediction method for mobile phone users based on an enhanced Markov Chain algorithm. The mobile phone data has a highly dynamic nature and a sparcely sampled aspect; therefore, the prediction of user's mobility location poses a challenge. Our enhancement approach can be summarized as an embedded association of rules applied to a Markov chain algorithm. The proposed solution is encouraging for the next generation of mobile networks and it can be used to optimize the existing mobile network infrastructure, road traffic, tracking systems and localization. Validation of our system was carried out using real data collected from the field.
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