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Understanding and Partitioning Mobile Traffic using Internet Activity Records Data - A Spatiotemporal Approach

机译:使用Internet活动记录数据的理解和分区移动流量 - 一种时空方法

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The internet activity records (IARs) of a mobile cellular network posses significant information which can be exploited to identify the network's efficacy and the mobile users' behavior. In this work, we extract useful information from the IAR data and identify a healthy predictability of spatio-temporal pattern within the network traffic. The information extracted is helpful for network operators to plan effective network configuration and perform management and optimization of network's resources. We report experimentation on spatiotemporal analysis of IAR data of the Telecom Italia. Based on this, we present mobile traffic partitioning scheme. Experimental results of the proposed model is helpful in modelling and partitioning of network traffic patterns.
机译:移动蜂窝网络的互联网活动记录(IARS)拥有重要信息,可以利用来识别网络的功效和移动用户行为。在这项工作中,我们从IAR数据中提取有用信息,并确定网络流量内的时空模式的健康可预测性。提取的信息有助于网络运营商计划有效的网络配置,并执行网络资源的管理和优化。我们举报了对电信ITALIA的IAR数据的时空分析试验。基于此,我们呈现了移动流量分区方案。所提出的模型的实验结果有助于网络流量模式的建模和分区。

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