Power Optimization of Large Scale Mobile Cloud Computing Systems

Abstract

The main objective of deploying large scale Mobile Cloud Computing (MCC) systems using the cloudlet based infrastructure is to reduce the total power consumption and the network delay while satisfying the Service Level Agreement (SLA). However, this objective is challenging to achieve due to the limited capabilities of the cloudlet system which limit the number of available services on each cloudlet system. This will force different cloudlets to cooperate in order to meet the users demands for different types of services. Moreover, the cooperation will require routing of user requests from the local cloudlet to a remote cloudlet that provide the requested service using a backbone network. This cooperation will increase the total power consumption per request which will include both the user to the local cloudlet power consumption and the power consumption for routing the request to a remote cloudlet. In this paper, we address the problem of optimizing the power consumption for large scale cooperative cloudlets deployments. The evaluation of the proposed model under different realistic scenarios shows that it can be used to accurately optimize power consumption in large scale MCC systems.