Resource-aware virtual machine migration in IoT cloud

Internet of Things (IoT) is a promising paradigm enabling many applications to network together through the internet. A huge volume of data is generated by such IoT applications for computation, storage, and analytics through the infrastructure and platform as service offered by cloud computing. Placement and execution of IoT applications in the cloud is a challenging task. In cloud-based IOT application, sudden changes in the sensing environment cause spikes of data flowing into the cloud. This causes resource starvation in the virtual machine and initiates migration of virtual machine from one physical server to other. However, unplanned migration causes a severe performance degradation to the application running on the cloud. Selection of suitable destination server for the virtual machine during migration is an important concern. This paper proposes a resource-aware virtual machine migration technique. Any sudden change in the sensing environment is observed by clustering the servers. The suitable target server is selected based on the resource utilization and job arrival rate of the destination server. The proposed technique is implemented in cloud platform running analytics on smart agriculture application. The evaluation results show that the proposed method outperforms the state of art techniques in terms of the number of migrations, energy utilization and migration time.