Abstract
Mobile devices are now capable of handling many daily computing tasks that used to be accomplished by desktops or servers. However, these improvements also introduce resource-hungry mobile applications that require richer resource-hungry computing features and more complex functions. Mobile Cloud Computing (MCC) addresses these limitations considering the nature of mobility; this innovative strategy provides external computing and storage capability so that tasks can be offloaded. The concept Cloudlet model is proposed to perform as the local resource pool that receives outsourced tasks. However, Cloudlets are restricted by the computing power and storage capacity, limiting the scale of offloading devices. In this paper, a Cloudlet-based task offloading model is proposed. By utilizing caching technologies and N-to-N resource scheduling, Cloudlets can support a larger number of mobile devices compared to previous models. Based on the experimental results, the proposed scheduling model cloud achieve better overall efficiency on energy consumption and task execution.