- Pelin Angin
Purdue University West Lafayette, Indiana, USA
pangin@cs.purdue.edu - Bharat Bhargava
Purdue University West Lafayette, Indiana, USA
bb@cs.purdue.edu
An Agent-based Optimization Framework for Mobile-Cloud Computing
The proliferation of cloud computing resources in the recent years offers a way for mobile devices with limited resources to achieve computationally intensive tasks in real-time. The mobile-cloud computing paradigm, which involves collaboration between mobile and cloud resources, is expected to become increasingly popular in mobile application development. Dynamic partitioning of applications between mobile and cloud platforms based on resource availability is crucial in achieving the best performance for any computationally intensive mobile application. In this paper, we propose a dynamic performance optimization framework for mobile-cloud computing utilizing mobile agent-based application partitions. The proposed framework imposes minimal infrastructural requirements on the cloud servers, therefore exhibiting widespread applicability, as opposed to previous approaches with stricter requirements. Experiments with two real-world mobile applications serve as an initial feasibility study of the proposed framework and demonstrate the superiority of the proposed approach over monolithic execution of resource-intensive applications on mobile devices.