Publication

Abstract : Mobile cloud computing offers computing, storage, and memory resources to mobile users through its high computing cloud servers. Mobile services are facilitated with efficient resource provisioning in the cloud. However, due to its inherent nature such as disconnections and limited battery life mobile users experience poor quality of service (QoS) in their connectivity with the cloud. This paper proposes an efficient request state aware resource provisioning technique that provisions the resources considering the current context information viz., battery, and connection quality of the mobile client. Various state viz., Accepted, Submitted and Running, Submitted and Paused, Resumed, Fulfilled, Rejected and Exit has been used to monitor the Client’s state. Besides, an intelligent resource capacity prediction technique based on a random forest algorithm has been incorporated to predict the future resource capacity requirement and schedule the client’s job in the cloud. The proposed technique has been implemented using CloudSim and analyzed using a mobile cloud storage dataset. Performance analysis proves that the proposed technique outperforms the state of art techniques in terms of waiting time, deadline violation, and accuracy of the prediction technique.