Scalable Cloudlet-based Mobile Computing Model

Abstract

Mobile Cloud Computing (MCC) has been introduced as a feasible solution to the inherited limitations of mobile computing. These limitations include battery lifetime, processing power and storage capacity. By using MCC, the processing and the storage of intensive mobile device jobs will take place in the cloud system and the results will be returned to the mobile device. This reduces the required power and time for completing such intensive jobs. However, connecting mobile devices with the cloud, suffers from the high network latency and the huge transmission power consumption especially when using 3G/LTE connections. On the other hand, multimedia applications are the most common applications in today's mobile devices; such applications require high computing resources. In this paper, a Cloudlet-based MCC system is introduced, aiming at reducing the power consumption and the network delay of multimedia applications while using MCC. The MCC concepts with the proposed Cloudlet framework are integrated and a new scalable framework for the MCC model is proposed. Our practical experimental results using multimedia applications show that using the proposed model reduces the power consumption of the mobile devices as well as reducing the communication latency when the mobile device requests a job to be performed remotely while satisfying the high quality of service requirements.