Thermal-Aware Coordinated Scheduling of Batch Workloads and Cooling Operations with Suspend–Resume Flexibility for Data Centers

Abstract

Data centers are under increasing pressure to improve operational efficiency amid growing computing demand and rising energy consumption. Among different workload types, batch workloads constitute an important source of scheduling flexibility because their execution can be adjusted over time while satisfying completion requirements. However, effective utilization of this flexibility requires explicit characterization of both the progressive and resumable nature of batchtask execution and the coupling among batch-task progression, thermal conditions, and cooling demand, which remain insufficiently addressed in existing studies. To bridge this gap, this paper develops an integrated model that unifies batchtask execution, server-side resource provisioning, and zone-level thermal-cooling dynamics. In this model, batch-task progress can be preserved across scheduling periods through suspendresume execution, while zone thermal states are explicitly incorporated to capture their influence on batch-task progression and cooling operation. The resulting coordinated scheduling problem is formulated to minimize data-center operating cost subject to workload completion and thermal safety constraints. Numerical results show that the proposed method reduces electricity cost, total energy consumption, peak power, and cooling burden while maintaining workload completion feasibility and thermal safety. Moreover, resumable execution and thermal-performance coupling are shown to provide complementary benefits, whose joint exploitation enables more efficient and balanced data-center operation.