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CET: Corner Extraction Technique for efficient characterization of GPS tracks

机译:CET:转角提取技术,可有效表征GPS轨迹

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The popularity of GPS sensors in mobile devices has enabled a new generation of location-based services, in which users record their traveling routes and upload the GPS track points (GTPs) on-the-fly for real-time social sharing, jog journaling, life logging, health care, and map generation. However, directly uploading all GTPs wastes battery energy and network bandwidth on the mobile device, because GTPs are highly redundant. To reduce the redundancies, we propose in this paper the Corner Extraction Technique (CET) to extract the corner points from the GTPs of individual users that can be used to characterize and reconstruct the routes that the user has traveled. Storing corner GTPs requires much less storage space, and transmitting them allows saving in both network bandwidth and energy consumption, leading to optimized GPS-enabled mobile applications. We have conducted both trace-driven simulations and real experiments to demonstrate the merits of the proposed CET approach. The experimental results indicate that: (1) CET results in up to 33 times of compression ratio, (2) CET closely follows the original road segments, and (3) CET saves energy consumption by up to 72%.
机译:GPS传感器在移动设备中的普及使新一代的基于位置的服务得以实现,用户可以记录他们的行驶路线并实时上传GPS跟踪点(GTP),以进行实时社交共享,慢跑日记,生命记录,医疗保健和地图生成。但是,直接上传所有GTP会浪费电池能量和移动设备上的网络带宽,因为GTP具有高度冗余性。为了减少冗余,我们在本文中提出了角点提取技术(CET),用于从单个用户的GTP中提取角点,这些角点可用于表征和重构用户所经过的路线。存储角落GTP所需的存储空间要少得多,传输它们可以节省网络带宽和能耗,从而优化了启用GPS的移动应用程序。我们已经进行了跟踪驱动的仿真和实际实验,以证明所提出的CET方法的优点。实验结果表明:(1)CET的压缩比高达33倍;(2)CET紧贴原始路段;(3)CET节省高达72%的能耗。

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