基于情景感知的Wi-Fi节能技术研究

发布时间：2018-03-16 22:31

本文选题：情景感知　切入点：Wi-Fi节能　出处：《内蒙古大学》2017年硕士论文　论文类型：学位论文

【摘要】：近年移动设备的不断发展,其功能也越发强大并且其内嵌很多传感器,比如位置传感器(GPS)、光学传感器等。正是因为移动设备的便利及功能的强大,用户会经常随身携带,所以通过内嵌在移动设备中的传感器收集到的数据可以更接近地体现出用户的一些日常习惯。而把通过某种途径比如通过移动设备获取到的环境数据称之为情景数据,如果对这些情景数据进行挖掘,建立情景感知系统模型,那么系统可以根据建立的模型为移动设备用户提供个性化、情景感知化的服务。而目前移动设备中Wi-Fi的耗能是许多手机用户热切关注的问题,尤其在用户不需要连接Wi-Fi而没有将其关闭,此时Wi-Fi模块需要不断的进行扫描从而导致不必要的电量浪费,因此可以通过解决不必要的Wi-Fi扫描以此达到节能效果。经过调研发现,用户连接Wi-Fi往往和用户每天所处的位置及时间有着密切联系,因此利用轨迹挖掘技术中的Apriori聚类算法挖掘用户频繁模式,再根据用户频繁点使用适合本系统的OPTICS密度算法检测用户Wi-Fi周期,为不同移动设备用户建立Wi-Fi周期情景感知模型,根据用户Wi-Fi周期模型提供智能开关Wi-Fi的服务,最终达到节能效果。实验结果显示,对于活动有规律的用户节约大约17%能量;活动规律一般的用户大约节约10%的能量。
[Abstract]:In recent years, the development of mobile devices, its function is more powerful and many embedded sensors, such as position sensor (GPS), optical sensors. It is because of the convenience and functionality of mobile devices and powerful, users will often carry through, so embedded in the mobile sensor device in the collected data to be close to some daily habits reflect the users. And through some channels such as mobile devices access to environmental data called the scene data, if the data mining of these scenarios, a context aware system model, then the system can be customized according to the established model for mobile device users, context aware services. At present, Wi-Fi energy consumption in mobile devices is that many mobile phone users are deeply concerned about the problem, especially in the user does not need to connect the Wi-Fi and will not be closed at Wi- The Fi module need to constantly scan the resulting in unnecessary power waste, so it can be solved by unnecessary Wi-Fi scans in order to achieve energy-saving effect. After the investigation found that users connect to Wi-Fi and often position and time the daily users are closely linked, because the use of Apriori clustering algorithm trajectory mining technology in mining user frequent pattern, according to the user's frequent use for the system OPTICS density detection algorithm of user Wi-Fi cycle, for users of different mobile devices to establish Wi-Fi cycle context aware model, providing intelligent switch Wi-Fi service according to the Wi-Fi cycle, the user model, finally to achieve energy-saving effect. The experimental results show that the activity for regular users to save about 17% energy the general rule of the user; activities about 10% of the energy saving.

【学位授予单位】：内蒙古大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN92

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