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Mining Time Series Data in Mobile Cellular Networks

机译:移动蜂窝网络中的采矿时间序列数据

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摘要

According to the ITU [2], the world population in 2006 amounted to 6.6 billion inhabitants, out of which, 923 million lived in Africa. The number of mobile subscribers sat at 198 million which amounted to nearly 7.2% of the worldwide mobile subscribers. Mobile telephony has been viewed as a critical enabling technology that is capable of boosting economies across Africa. However, Africa accounted for only 14% of the worldwide Gross Domestic Product (GDP) in 2006 [2]. With the varying socio-economic distributions that is prevalent in most African countries, an accurate mechanism that is able to determine traffic trends in a mobile cellular network based on subscriber behaviour would be beneficial to an operator for planning of network demand. With the availability of large amounts of data from existing networks, data mining techniques that are able to retrieve meaningful information that is beneficial to a network planner would be useful. This paper looks at the benefits of using data mining in time-series databases for the determination of traffic trends in mobile cellular networks.
机译:根据国际电联[2],2006年的世界人口达到66亿居民,其中,在非洲生活9.23亿。移动用户人数均为198,000万,占全球移动订阅者的近7.2%。移动电话已被视为一种关键的支持技术,能够跨非洲推动经济。但是,2006年,非洲占全球国内生产总值(GDP)的14%[2]。随着大多数非洲国家的不同的社会经济分布,能够根据用户行为确定移动蜂窝网络中交通趋势的准确机制将有利于运营商进行网络需求。随着来自现有网络的大量数据的可用性,能够检索有意义对网络规划器有意义的有意义信息的数据挖掘技术将是有用的。本文介绍在时间序列数据库中使用数据挖掘的好处,以确定移动蜂窝网络中的交通趋势。

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