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Energy Consumption Reduction via Context-Aware Mobile Video Pre-fetching

机译:通过上下文感知移动视频预取减少能量消耗减少

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The arrival of smart phones and tablets, along with a flat rate mobile Internet pricing model have caused increasing adoption of mobile data services. According to recent studies, video has been the main driver of mobile data consumption, having a higher growth rate than any other mobile application. However, streaming a medium/high quality video files can be an issue in a mobile environment where available capacity needs to be shared among a large number of users. Additionally, the energy consumption in mobile devices increases proportionally with the duration of data transfers, which depend on the download data rates achievable by the device. In this respect, adoption of opportunistic content pre-fetching schemes that exploit times and locations with high data rates to deliver content before a user requests it, has the potential to reduce the energy consumption associated with content delivery and improve the user's quality of experience, by allowing playback of pre-stored content with virtually no perceived interruptions or delays. This paper presents a family of opportunistic content pre-fetching schemes and compares their performance to standard on-demand access to content. By adopting a simulation approach on experimental data, collected with monitoring software installed in mobile terminals, we show that content pre-fetching can reduce energy consumption of the mobile devices by up to 30% when compared to the on demand download of the same file, with a time window of 1 hour needed to complete the content prepositioning.
机译:智能手机和平板电脑的到来以及平衡率移动互联网定价模型造成了增加的移动数据服务的采用。根据最近的研究,视频一直是移动数据消耗的主要驱动因素,比任何其他移动应用程序都具有更高的增长率。但是,流式传输中/高质量的视频文件可以是移动环境中的问题,其中需要在大量用户之间共享可用容量。另外,移动设备中的能量消耗随数据传输的持续时间比例地增加,这取决于设备可实现的下载数据速率。在这方面,通过机会主义内容预取计划,该方法利用高数据速率的利用时间和位置来提供内容在用户请求之前提供内容,这有可能降低与内容传递相关的能量消耗,并提高用户的体验质量,通过播放预先存储的内容,几乎没有感知的中断或延迟。本文介绍了一系列机会主义内容预取计划,并将其性能与标准的按需访问权限进行了比较。通过采用在实验数据上进行模拟方法,通过安装在移动终端中安装的监控软件,我们显示内容预取可以将移动设备的能耗降低到同一文件的按需下载时高达30%,使用1小时的时间窗口来完成内容介词。

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