High-speed REPTA algorithm for performance cost optimization in data centers considering workload delay tolerances

The rapid development of data centers (DTCs) has led to substantially increased energy consumption and electricity bills. Thus, this paper aims to minimize the performance costs of geographically distributed DTCs. Firstly, an integrated electricity-heat system model for geographically-distributed DTCs is developed considering renewable energy sources (RESs) and waste heat recovery. Particularly, the differences of delay tolerances in computational tasks are fully considered in the developed model, which aligns with real-world DTCs. Further, to cope with the large-scale decision variables caused by the delay tolerance model, a RES and electricity price aware task assignment (REPTA) algorithm based three-stage energy dispatch strategy is presented, which accelerates the decision-making process. In stage I, an electricity-heat coordinated optimization (EHCO) model is constructed, which preliminarily determines the scheduling plan with the exclusion of delay-tolerant tasks. In stage II, the REPTA algorithm is designed to allocate delay-tolerant tasks according to the complementarities of electricity prices and RESs. Then in stage III, incorporating the task allocation results of stage II, the EHCO model is solved again to obtain the ultimate energy dispatch decisions. Finally, the proposed solution is assessed through comparative experiments based on the data from Parallel Workloads Archive, and the numerical results confirm its effectiveness in both environmental and economic indicators.