In this paper, we propose a novel electricity cost capping algorithm that not only minimizes the electricity cost of operating cloud-scale data centers, but also enforces a cost budget on the monthly electricity bill. Our solution first explicitly models the impacts of power demands on electricity prices and the power consumption of cooling and networking in the minimization of electricity cost. In the second step, if the electricity cost exceeds a desired monthly budget due to unexpectedly high workloads, our solution guarantees the quality of service for premium customers and trades off the request throughput of ordinary customers. We formulate electricity cost capping as two related constrained optimization problems and propose an efficient algorithm based on mixed integer programming. Simulation results show that our solution outperforms the state-ofthe-art solutions by having lower electricity costs and achieves desired cost capping with maximized request throughput.
In a recent study, Zhang et al. REF propose an electricity bill capping algorithm to minimize the electricity cost within the cost budget for data center networks.
Capping the electricity cost of cloud-scale data centers with impacts on power markets
HPDC '11
Computer Science