A Genetic Algorithm for Virtual Machine Migration in Heterogeneous Mobile Cloud Computing

Mobile Cloud Computing (MCC) improves the performance of a mobile application by executing it at a resourceful cloud server that can minimize execution time compared to a resource-constrained mobile device. Virtual Machine (VM) migration in MCC brings cloud resources closer to a user so as to further minimize the response time of an offloaded application. Such resource migration is very effective for interactive and real-time applications. However, the key challenge is to find an optimal cloud server for migration that offers the maximum reduction in computation time. In this paper, we propose a Genetic Algorithm (GA) based VM migration model, namely GAVMM, for heterogeneous MCC system. In GAVMM, we take user mobility and load of the cloud servers into consideration to optimize the effectiveness of VM migration. The goal of GAVMM is to select the optimal cloud server for a mobile VM and to minimize the total number of VM migrations, resulting in a reduced task execution time. Additionally, we present a thorough numerical evaluation to investigate the effectiveness of our proposed model compared to the state-of-the-art VM migration policies.