Abstract
With the rapid development of mobile internet, it’s essential to understand the spatial-temporal distribution of mobile traffic. Based on the mobile traffic data collected from a large 4G cellular network in northwestern China, this paper presents detailed analyses of the traffic data on base stations in two aspects: (1) spatial-temporal distribution, (2) clustering based on physical context, i.e., urban function. We introduce the concept of traffic density to measure the traffic level, according to the Voronoi diagram to partition the covering area of BSs. Both spatial and temporal dimensions show distinct inhomogeneity property of mobile traffic. Furthermore, we cluster BSs utilizing urban function information, which enables us to identify and label base stations. The diverse application usage patterns of each cluster of BSs are obtained, which could be applied in resource cache policy and BS loading allocation.
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Acknowledgements
This work is supported by the National Science Foundation of China (NSFC) under grant 61571054, 61771065 and 61631005, by the New Star in Science and Technology of Beijing Municipal Science and Technology Commission (Beijing Nova Program: Z151100000315077).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Wang, T., Zhang, X., Wang, W. (2018). Spatial-Temporal Distribution of Mobile Traffic and Base Station Clustering Based on Urban Function in Cellular Networks. In: Li, C., Mao, S. (eds) Wireless Internet. WiCON 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-319-90802-1_26
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DOI: https://doi.org/10.1007/978-3-319-90802-1_26
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