Cracow University of Technology
Data-aware scheduling in today's large-scale computing systems has become a major complex research issue. This problem becomes even more challenging when data is stored and accessed from many highly distributed servers and energy-efficiency is treated as a main scheduling objective. In this paper, the authors approach the independent batch scheduling in grid environment as a bi-objective minimization problem with makespan and energy consumption as the scheduling criteria. They used the Dynamic Voltage and Frequency Scaling (DVFS) model for reducing the cumulative power energy utilized by the system resources for tasks executions.