Joint Host-Network Power Scaling with Minimizing VM Migration in SDN-enabled Cloud Data Centers

Abstract

In recent times, both industry and academia have paid significant attention to the power management of cloud data centers (CDCs), due to their typically very high electrical energy consumption. While servers remain the components with the highest power-consumption, network stacks can also consume about 10-20 percent of the total energy usage in a data center. Dynamic Virtual Machine (VM) consolidation is one way to reduce the number of active servers, which can be done by live migration of the VMs. But, migration operations in a data center bring several system and service level overheads that include downtime, elephant flows over the network, and potentially higher failure rates. In this work, we propose algorithms for minimizing the number of VM migrations to attain the optimized joint host-network power consumption in a cloud data center. We present a trade-off between the number of migrations, the joint host-network power consumption, and the computational time complexity of the proposed algorithms. Using Mininet and ONOS, an SDN enabled framework is utilised to evaluate the proposed algorithms. Experimental results show that our algorithms can reduce power consumption by about 11 percent, while completing between 18 to 25 percent more VM migrations compared to the baseline algorithm, which only minimizes migration without guaranteeing lowest power consumption.