Domain-wide recognized by their high value in human presence and activity studies, cellular network datasets (i.e., Charging Data Records, named CdRs), however, present accessibility, usability, and privacy issues, restricting their exploitation and research reproducibility.This paper tackles such challenges by modeling Cdrs that fulfill real-world data attributes. Our designed framework, named Zen follows a four-fold methodology related to (i) the LTSM-based modeling of users' traffic behavior, (ii) the realistic and flexible emulation of spatiotemporal mobility behavior, (iii) the structure of lifelike cellular network infrastructure and social interactions, and (iv) the combination of the three previous modules into realistic Cdrs traces with an individual basis, realistically. Results show that Zen's first and third models accurately capture individual and global distributions of a fully anonymized real-world Cdrs dataset, while the second model is consistent with the literature's revealed features in human mobility. Finally, we validate Zen Cdrs ability of reproducing daily cellular behaviors of the urban population and its usefulness in practical networking applications such as dynamic population tracing, Radio Access Network's power savings, and anomaly detection as compared to real-world CdRs.
翻译:以人类存在和活动研究、手机网络数据集(即充电数据记录,名为CdRs)等高价值为特征的全域域认识,然而,本文通过模拟实现真实世界数据属性的Cdrers模型处理这些挑战。我们设计的Zen名为Zen的框架采用了四倍的方法,涉及(一) 以LTSM为基础的用户交通行为模型,(二) 现实和灵活地模拟空间流动行为,(三) 类似生命的蜂窝网络基础设施和社会互动的结构,以及(四) 将前三个模块结合成现实的Cdrers跟踪,以个人为基础,现实地进行。结果显示Zen的第一和第二模型准确地捕捉了完全匿名的真实世界Cdrers数据集的个人和全球分布,而第二个模型与文献所揭示的人类流动特征相一致。最后,我们验证Zen Cdrrrs在复制日常细胞行为的能力,将城市人口的实际储蓄和实用性网络化,作为城市人口的实际动态网络的检索工具,将进入城市人口的实际动态网络,进入真实性网络。