Priority-based virtual machine load balancing in a scientific federated cloud

Cloud computing offers utility oriented services to users. It also reduces the maintenance cost of the infrastructure as well as initial investment cost for users or startup companies. Due to the effectiveness of these services, many companies or institutes are trying to adopt this technology for offloading scientific or industrial applications. Virtualization in cloud computing is used to build virtual infrastructure which is managed by a load balancer. Efficient design of the load balancer can reduce over or under provisioning. Load balancer contains virtual machine allocation technique which performs an important role with respect to power consumption of the data center. In this paper, we propose a system architecture and the virtual machine allocation algorithm for the load balancer in a scientific federated cloud. We have tested the proposed approach in a scientific federated cloud. Experimental results show that the proposed algorithm not only increases the utilization of resources but also reduces the energy consumption.