• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Providing a Better Computing Experience While Preserving Data Privacy Through Hardware, Software and Data Partitioning in Pervasive Computing Environments.
【24h】

Providing a Better Computing Experience While Preserving Data Privacy Through Hardware, Software and Data Partitioning in Pervasive Computing Environments.

机译：在普及的计算环境中提供更好的计算体验，同时通过硬件，软件和数据分区保护数据隐私。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Mobile devices, smartphones and tablets, have become an integral part of everyday life, allowing users to be connected and perform all sorts of computing tasks. Despite being quite powerful, smartphones and tablets are not as capable as desktops and laptops due to their small form factor and limited power, and this difference is likely to persist for a number of years. To bridge the gap, researchers and developers have started incorporating external resources such as remote nodes on the local network or the Internet and the Cloud in performing computing tasks using mobile devices. This entails offloading a part or all of a computing task to a remote node that performs the task and returns the results back to the mobile device. This allows users to perform tasks through their mobile devices that are not possible or impractical to be performed on mobile devices alone. However, offloading introduced several new challenges such as resource discovery and use, node security, and data privacy.;This dissertation discusses how partitioning can be used to provide a better computing experience to mobile users addressing the challenges related to offloading. Hardware limitation of mobile devices is addressed by providing a solution that allows the mobile user to easily build a personal computing environment by integrating several remote resources into one Logical Machine. To address the issue of user data privacy when data is shipped to untrusted remote nodes, a new approach of user-specified data partitioning is introduced. The overall execution consists of identifying sensitive data, shipping code and non-private data for remote execution and getting the results back, and then combining the results from local and remote executions on the mobile device. This approach is validated via three popular applications, image processing, audio processing and video processing applications developed for Android platform.
机译：移动设备，智能手机和平板电脑已成为日常生活不可或缺的一部分，使用户可以连接并执行各种计算任务。尽管智能手机和平板电脑功能强大，但由于其外形小巧，功能有限，其功能不如台式机和笔记本电脑，而且这种差异可能会持续多年。为了缩小差距，研究人员和开发人员已开始将外部资源（例如本地网络或Internet和云上的远程节点）整合到使用移动设备执行计算任务中。这需要将部分或全部计算任务卸载到执行该任务的远程节点，并将结果返回给移动设备。这允许用户通过他们的移动设备执行不可能仅在移动设备上执行的任务或不切实际的任务。但是，卸载带来了资源发现和使用，节点安全性以及数据隐私等几个新挑战。本论文讨论了如何使用分区为移动用户提供更好的计算体验，以解决与卸载相关的挑战。通过提供一种解决方案来解决移动设备的硬件限制，该解决方案允许移动用户通过将多个远程资源集成到一台逻辑机中来轻松构建个人计算环境。为了解决将数据发送到不受信任的远程节点时用户数据隐私的问题，引入了一种新的用户指定数据分区方法。总体执行包括识别敏感数据，运输代码和非私有数据以进行远程执行并取回结果，然后将移动设备上本地和远程执行的结果组合在一起。通过为Android平台开发的三个流行应用程序（图像处理，音频处理和视频处理应用程序）验证了此方法。

著录项

  • 作者

    Al-Mutawa, Mohammad.;

  • 作者单位

    University of Colorado at Boulder.;

  • 授予单位 University of Colorado at Boulder.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 120 p.
  • 总页数 120
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号