Research Area: Mobile Cloud Computing
Rapid advancement in the mobile telecommunications industry has motivated the development of mobile applications in a wide range of social and scientific domains. However, mobile computing (MC) platforms still have several constraints, such as limited computation resources, short battery life and high sensitivity to network capabilities. In order to overcome the limitations of mobile computing and benefit from the huge advancement in mobile telecommunications and the rapid revolution of distributed resources, mobile-aware computing models, such as mobile cloud computing (MCC) and mobile edge computing (MEC) have been proposed. The main problem is to decide on an application execution plan while satisfying quality of service (QoS) requirements and the current status of system networking and device energy.
These frameworks and techniques are proposed to provide optimised solutions to schedule data intensive mobile applications. Experimental results show the ability of the proposed tools in optimising the scheduling and the execution of data intensive applications on various computing environments to meet application QoS requirements. Furthermore, the results clearly stated the significant contribution of the data size parameter on scheduling the execution of mobile applications. In addition, the thesis provides an analytical investigation of mobile-aware computing environments for a certain mobile application type. The investigation provides performance analysis to help users decide on target computation resources based on application structure, input data, and mobile network status.
Name of the Researcher: Alkhalaileh, Mohammad
Name of the Supervisor(s): Bahman Javadi
Year of Completion: 2021
University: Western Sydney University
Thesis Link: Home Page Url
