Abstract:
This thesis contributes in a major way to the mainstream efforts that aim to realize the goals of LTE Advanced (LTE-A), which in turn were set to reach data rates that near 1 Gigabits per second in the downlink and 500 Megabits per second in the uplink for the future wireless communication networks. This work adapts the paradigm of Cloud Computing over the framework of Device-to-Device (D2D) proximal communications in order to offload major traffic volumes from the core network and thus enable it to grant higher data rates to mobile users. Existing approaches to the evolution of cellular network technologies have been driven by the ever-increasing need for capacity and coverage. Our proposed work introduces a platform in which mobile devices, mostly smart phones, can offer network services to other nearby devices, and thus acts as service end points (providers), thus resembling in this respect to hotspots. Hence, proximity-based D2D is accomplished while at the same time, the service provider mobile devices form transient focal points in the network, and hence act as dynamic base stations, or in Cloud Computing terminology, Cloudlets. With the Cloud Computing interface, mobile devices seeking particular services can discover providers and subsequently communicate with them directly, but with the help of the network whose role is limited to assisting in the service provider discovery process. In this way, our platform will serve to shift wireless network traffic from the core network, and thus achieve the objective of traffic offloading, but perhaps more importantly, serve the community at large by creating an environment of widespread collaboration among mobile users. This capability can introduce several positive aspects within any community, through 1) helping tourism and foreign nationals by making it simple and seamless to obtain needed services; 2) improving social ties among the members of the society; and of course 3) helping the economy through creating a more conducive environment for thriving business
Description:
Thesis. M.E. American University of Beirut. Department of Electrical and Computer Engineering, 2015. ET:6158
Advisor : Dr. Hassan Artail, Professor, Electrical and Computer Engineering ; Members of Committee : Dr. Zaher Dawy, Professor, Electrical and Computer Engineering ; Dr. Haidar Safa, Associate Professor, Computer Science.
Includes bibliographical references (leaves 113-116)