Overbooking-based resource allocation in virtualized data center

Efficient resource management in the virtualized data center is always a practical concern and has attracted significant attention. In particularly, economic allocation mechanism is desired to maximize the revenue for commercial cloud providers. This paper uses overbooking from Revenue Management to avoid resource over-provision according to its runtime demand. We propose an economic model to control the overbooking policy while provide users probability based performance guarantee using risk estimation. To cooperate with overbooking policy, we optimize the VM placement with traffic-aware strategy to satisfy application's QoS requirement. We design GreedySelePod algorithm to achieve traffic localization in order to reduce network bandwidth consumption, especially the network bottleneck bandwidth, thus to accept more requests and increase the revenue in the future. The simulation results show that our approach can greatly improve the request acceptance rate and increase the revenue by up to 87% while with acceptable resource confliction.