Location-aware mobile social networking for video sharing

Resource type
Thesis type
((Thesis)) M.Sc.
Date created
Author: Ma, Li
Location information improves the routing effectiveness and facilitates the development of diverse novel applications in mobile networking. Although more people enjoy Internet and multimedia via their cell phones, most of the services for online video sharing are still restricted to traditional PC users. The existing systems of mobile video sharing have yet to effectively explore mobility decently or address the energy and bandwidth limitations of mobile devices. Furthermore, while such location information can lead to better user experiences, given privacy concerns and hardware constraints, a mobile user often exposes a limited number of locations only. We are thus interested in the Trajectory Exposure Problem in this context, i.e., to what degree that the user's trajectory (i.e., its route) is exposed? Furthermore, can the user adaptively control the exposure of its trajectory and yet offer useful information for location-based services? In this thesis, we first propose MoViShare (Mobile Video Share), a universal video sharing platform that will provide anytime anywhere video browsing and publishing services for mobile devices. MoViShare targets to create and maintain location-aware mobile social networks, and to apply video abstraction technique for saving bandwidth and energy. We extend it with another project Scoop as the enhancement for professional uses. We then explore Gaussian Process Regression, an effective tool to re-construct the trajectory of the mobile user with selected exposed locations. We examine how the re-constructed trajectory differs from the real trajectory, i.e., evaluating the exposure rate. We present an effective heuristic that adaptively controls the trajectory exposure rate by carefully choosing the exposed locations. We further demonstrate a practical routing protocol, MoRPTE, which, controlled by a single parameter, utilizes location information flexibly and adaptively in the spectrum from zero knowledge to full knowledge to fit the applications' demands.
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Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Liu, Jiangchuan
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etd6743_LMa.pdf 3.76 MB