發(fā)布時(shí)間：2018-03-16 22:31

  本文選題：情景感知　切入點(diǎn)：Wi-Fi節(jié)能　出處：《內(nèi)蒙古大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：近年移動(dòng)設(shè)備的不斷發(fā)展,其功能也越發(fā)強(qiáng)大并且其內(nèi)嵌很多傳感器,比如位置傳感器(GPS)、光學(xué)傳感器等。正是因?yàn)橐苿?dòng)設(shè)備的便利及功能的強(qiáng)大,用戶會(huì)經(jīng)常隨身攜帶,所以通過(guò)內(nèi)嵌在移動(dòng)設(shè)備中的傳感器收集到的數(shù)據(jù)可以更接近地體現(xiàn)出用戶的一些日常習(xí)慣。而把通過(guò)某種途徑比如通過(guò)移動(dòng)設(shè)備獲取到的環(huán)境數(shù)據(jù)稱之為情景數(shù)據(jù),如果對(duì)這些情景數(shù)據(jù)進(jìn)行挖掘,建立情景感知系統(tǒng)模型,那么系統(tǒng)可以根據(jù)建立的模型為移動(dòng)設(shè)備用戶提供個(gè)性化、情景感知化的服務(wù)。而目前移動(dòng)設(shè)備中Wi-Fi的耗能是許多手機(jī)用戶熱切關(guān)注的問(wèn)題,尤其在用戶不需要連接Wi-Fi而沒(méi)有將其關(guān)閉,此時(shí)Wi-Fi模塊需要不斷的進(jìn)行掃描從而導(dǎo)致不必要的電量浪費(fèi),因此可以通過(guò)解決不必要的Wi-Fi掃描以此達(dá)到節(jié)能效果。經(jīng)過(guò)調(diào)研發(fā)現(xiàn),用戶連接Wi-Fi往往和用戶每天所處的位置及時(shí)間有著密切聯(lián)系,因此利用軌跡挖掘技術(shù)中的Apriori聚類算法挖掘用戶頻繁模式,再根據(jù)用戶頻繁點(diǎn)使用適合本系統(tǒng)的OPTICS密度算法檢測(cè)用戶Wi-Fi周期,為不同移動(dòng)設(shè)備用戶建立Wi-Fi周期情景感知模型,根據(jù)用戶Wi-Fi周期模型提供智能開(kāi)關(guān)Wi-Fi的服務(wù),最終達(dá)到節(jié)能效果。實(shí)驗(yàn)結(jié)果顯示,對(duì)于活動(dòng)有規(guī)律的用戶節(jié)約大約17%能量;活動(dòng)規(guī)律一般的用戶大約節(jié)約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.

【學(xué)位授予單位】：內(nèi)蒙古大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN92

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本文編號(hào)：1621921