Abstract
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, storage space, and network bandwidth on the mobile device, because GTPs are highly redundant. To reduce the redundancies, we propose in this thesis 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. Such features are especially attracted for the emerging wearable devices. 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%.