Research Area: Mobile Cloud Computing
The current proliferation of mobile systems, such as smart phones, PDA and tablets, has led to their adoption as the primary computing platforms for many users. This trend suggests that designers will continue to aim towards the convergence of functionality on a single mobile device. However, this convergence penalizes the mobile system in computational resources such as processor speed, memory consumption, disk capacity, as well as in weight, size, ergonomics and the user’s most important component, battery life. Therefore, this current trend aims towards the efficient and effective use of its hardware and software components. Hence, energy consumption and response time are major concerns when executing complex algorithms on mobile devices because they require significant resources to solve intricate problems.
To this end, this thesis quantitatively and qualitatively compares the performance of executing two different kinds of workloads locally on two different mobile devices and remotely on two different cloud computing providers. The results of this thesis are expected to provide valuable insight to developers and architects of mobile applications by providing information on the applications that can be performed remotely in order to save energy and get better response times while remaining transparent to users.
Name of the Researcher: Jesus Zambrano
Name of the Supervisor(s): Sanjay P. Ahuja
Year of Completion: 2015
University: University of North Florida
Thesis Link: Home Page Url
