Dynamic Deferral of Workload for Capacity Provisioning in Data Centers

Recent increase in energy prices has led researchers to find better ways for capacity provisioning in data centers to reduce energy wastage due to the variation in workload. This paper explores the opportunity for cost saving and proposes a novel approach for capacity provisioning under bounded latency requirements for the workload. We investigate how many servers to be kept active and how much workload to be delayed for energy saving while meeting every deadline. We present an offline LP formulation for capacity provisioning by dynamic deferral and give two online algorithms to determine the capacity of the data center and the assignment of workload to servers dynamically. We prove the feasibility of the online algorithms and show that their worst case performance are bounded by a constant factor with respect to the offline formulation. We validate our algorithms on synthetic workload generated from two real HTTP traces and show that they actually perform much better in practice than the worst case, resulting in 20-40% cost-savings.