Thermal aware workload scheduling with backfilling for green data centers

Abstract

Data centers now play an important role in modern IT infrastructures. Related research has shown that the energy consumption for data center cooling systems has recently increased significantly. There is also strong evidence to show that high temperatures with in a data center will lead to higher hardware failure rates and thus an increase in maintenance costs. This paper devotes itself in the field of thermal aware resource management for data centers. This paper proposes an analytical model, which describes data center resources with heat transfer properties and workloads with thermal features. Then a thermal aware task scheduling algorithm with backfilling is presented which aims to reduce power consumption and temperatures in a data center. A simulation study is carried out to evaluate the performance of the algorithm. Simulation results show that our algorithm can significantly reduce temperatures in data centers by introducing endurable decline in performance.