Greenway: Joint Vm Placement And Topology Adaption For Green Data Center Networking

Energy consumption has become a key issue for running large-scale data center networks (DCN) nowadays. Previous studies mainly focus on energy saving through reducing the number of active servers or network switches with traffic consolidation. However, since this mechanism benefits from the routing flexibility, both the gained energy savings and flow performance are limited by the conventional static network topology. Recent advances in DCN architecture propose to implement an adaptive network topology with reconfigurable optical/wireless links (i.e., topology-adaptive DCNs), which has shown a great potential to improve the transmission performance of existing static wired network. In this paper, we propose GreenWay, an energy-efficient solution to jointly optimize the virtual machine (VM) placement and flow transmissions under the new paradigm of topology adaption. Based on the VM traffic demands, it can construct a proper run-time network topology to lower both the energy cost and communication cost among VMs. We first formulate the energy optimization problem in topology-adaptive DCNs. After showing the its NP-hardness, we then develop heuristic algorithms to address the VM placement and topology adaption effectively. Extensive trace-based simulations show that GreenWay consumes much less energy than other state-of-th-eart solutions while ensuring better flow performance. We finally implement an OpenvSwitch-based testbed and demonstrate the efficiency of our solution.