PROJECT TITLE :

Economic and Energy Considerations for Resource Augmentation in Mobile Cloud Computing - 2018

ABSTRACT:

In earlier works [one], [two], we have a tendency to proposed to utilize a centralized broker-node to perform task scheduling for the resource augmentation of a big number of mobile devices. The task scheduler model centered on energy optimization was proposed for the centralized task scheduling problem. During this Project, the model extends the optimization process by including an economic part to it. Therefore, we propose an energy and financial value-aware mathematical task scheduler model. Compared to the previous model, this model, will permit mobile devices to offload multiple tasks to cloud resources. The leads to this Project are additional thorough and additional aspects of task offloading have been analysed. As an example, the model is evaluated beneath two different resource augmentation environments for mobile cloud computing: a native private cloud and public clouds. More precisely, the task scheduling downside is optimally solved to minimize: (i) the whole energy consumption when applied to a local non-public cloud, and (ii) the entire energy consumption and monetary price when applied to public clouds. Our proposed model at the centralized broker-node finds optimal solutions for task assignment drawback, and provides a significant reduction in the entire costs compared with the task assignment by the centralized scheduler while not optimization.