Virtual Machine Migration: A Resource Intensive Outsourcing Mechanism for Mobile Cloud Computing

TL;DR

This paper empirically analyzes how VM deployment and management impact application execution time and resource usage in mobile cloud computing, highlighting the heavyweight nature of VM-based offloading on smart devices.

Contribution

It provides an empirical evaluation of VM deployment and management effects on application performance in MCC using CloudSim simulations, emphasizing resource overheads.

Findings

VM deployment and management increase resource consumption on SMDs.

Application execution time is significantly affected by VM management overhead.

VM-based offloading is resource-intensive and may be heavyweight for mobile devices.

Abstract

In Mobile Cloud Computing (MCC), Virtual Machine (VM) migration based process offloading is a dominant approach to enhance Smart Mobile Devices (SMDs). A challenging aspect of VM deployment is the additional computing resources usage in the deployment and management of VM which obliges computing resources for VM creation and configuration. The management of VM comprises computing resources exploitation in the monitoring of VM in entire lifecycle and physical resources management for VM on SMDs. Therefore, VM migration based application offloading requires additional computing resource. Consequently computing resources demand and execution time of the application increases respectively. In this paper, we empirically review the impact of VM deployment and management on the execution time of application in diverse scenarios. We investigate VM deployment and management for application processing in simulation environment by employing CloudSim: a simulation toolkit that provides an extensible simulation framework to model VM deployment and management for application processing in cloud infrastructure. The significance of this work is to ensure that VM deployment and management necessitates additional computing resources on SMD for application offloading. We evaluate VM deployment and management in application processing by analyzing Key Performance Parameters (KPPs) in different scenarios; such as VM deployment, the execution time of applications, and total execution time of the simulation. We use KPPs to assess deviations in the results of diverse experimental scenarios. The empirical analysis concludes that VM deployment and management oblige additional resources on computing host which make it a heavyweight approach for process offloading on smart mobile device.