Enhancing service capability with multiple finite capacity server queues in cloud data centers

Cloud computing took a step forward in the efficient use of hardware through virtualization technology. And as a result, cloud brings evident benefits for both users and providers. While users can acquire computational resources on-demand elastically, cloud vendors can also utilize maximally the investment costs for data centers infrastructure. In the Internet era, the number of appliances and services migrated to cloud environment increases exponentially. This leads to the expansion of data centers, which become bigger and bigger. Not just that these data centers must have the architecture with a high elasticity in order to serve the huge upsurge of tasks and balance the energy consumption. Although in recent times, many research works have dealt with finite capacity for single job queue in data centers, the multiple finite-capacity queues architecture receives less attention. In reality, the multiple queues architecture is widely used in large data centers. In this paper, we propose a novel three-state model for cloud servers. The model is deployed in both single and multiple finite capacity queues. We also bring forward several strategies to control multiple queues at the same time. This approach allows to reduce service waiting time for jobs and managing elastically the service capability for the whole system. We use CloudSim to simulate the cloud environment and to carry out the experiments in order to demonstrate the operability and effectiveness of the proposed method and strategies. The power consumption is also evaluated to provide insights into the system performance in respect of performance-energy trade-off.