Energy-Efficient Real-Time Tasks Scheduling in Cloud Data Centers

Abstract

Reducing energy consumption in cloud computing systems has been a major concern among the researchers because it not only reduce the operational cost but also increase the system reliability, and efficient scheduling approach is a promising way to achieve this goal. But unfortunately, existing energy-aware scheduling approaches are inadequate  for real-time tasks running in cloud environment because they assumes that cloud computing environment are deterministic and pre-computed schedule decisions are followed  during the execution. The above issues are addressed in this paper by considering the number of energy-efficiency factors such as energy cost, CPU power efficiency, carbon emission rate, and workload, and near-optimal energy efficient scheduling policies are proposed for cloud data center for scheduling real-time, aperiodic, independent tasks that can reduce operational cost and provide Quality of Service (QoS)