Enhanced Adaptive Cloudlet Placement Approach for Mobile Application on Spark

Abstract

The applications of mobile devices are increasingly becoming computationally intensive while the computing capability of the user's mobile device is limited. Traditional approaches offload the tasks of mobile applications to the remote cloud. However, the rapid growth of mobile devices has made it a challenge for the remote cloud to provide computing and storage capacities with low communication delays due to the fact that the remote cloud is geographically far away from mobile devices. Reducing the completion time of applications in mobile devices through the technical expending mobile cloudlets which are moving collocated with Access Points (APs) is necessary. To address the above issues, this paper proposes EACP-CA (Enhanced Adaptive Cloudlets Placement approach based on Covering Algorithm), an enhanced adaptive cloudlet placement approach for mobile applications in a given network area. We apply the CA (Covering Algorithm) to adaptively cluster the mobile devices based on their geographical locations, the aggregation regions of the mobile devices are identified, and the cloudlet destination locations are also confirmed according to the clustering centers. In addition, we can also obtain the traces between the original and destination locations of these mobile cloudlets. To increase the efficiency, we parallelize CA on Spark. Extensive experiments show that the proposed approach outperforms the existing approach in both effectiveness and efficiency.