temperature-aware dynamic resource provisioning in a power-optimized datacenter
The current energy and environmental cost trends of datacenters are unsustainable. It is critically important to develop datacenter-wide power and thermal management (PTM) solutions that improve the energy efficiency of the datacenters. This paper describes one such approach where a PTM engine decides on the number and placement of ON servers while simultaneously adjusting the supplied cold air temperature. The goal is to minimize the total power consumption (for both servers and air conditioning units) while meeting an upper bound on the maximum temperature seen in any server chassis in the data center. To achieve this goal, it is important to be able to predict the incoming workload in terms of requests per second (which is done by using a short-term workload forecasting technique) and to have efficient runtime policies for bringing new servers online when the workload is high or shutting them off when the workload is low. Datacenter-wide power saving is thus achieved by a combination of chassis consolidation and efficient cooling. Experimental results demonstrate the effectiveness of the proposed dynamic resource provisioning method.
resource provisioning datacenter energy efficient cloud computing temperature aware power optimization