Energy-Optimized Dynamic Deferral of Workload for Capacity Provisioning in Data Centers
In this paper, the authors explores the opportunity for energy cost saving in data centers that utilizes the flexibility from the Service Level Agreements (SLAs) and proposes a novel approach for capacity provisioning under bounded latency requirements of the workload. They investigate how many servers to keep active and how much workload to delay for energy saving while meeting latency constraints. They 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. They prove the feasibility of the online algorithms and show that their worst case performances are bounded by constant factors with respect to the offline formulation.