Energy-Aware Scheduling of Multiple Workflows Application on Distributed Systems

In this paper, the important issue of workflow scheduling on a large-scale distributed system, to achieve the scheduling quality and the energy consumption, is addressed. Since the traditional scheduling focused on minimizing the execution time and not takes the energy consumption into account, developing a scheduling for achieving both objectives has become a challenge issue. In addition, the computing resources are shared in the large-scale system, scheduling of multiple workflow application further complicate. The efficient multiple workflows scheduling with energy-aware is called EMuWS is addressed the challenge. The proposed algorithm, to efficiently determine the inefficient processors and shut them down for reducing computing resources, is adopted by the RE and cost function, which is the threshold of resource reduction. After a set of the efficient processors known, the workflow is rescheduled to assign fewer processors to attain more energy efficiency. The performance of the proposed algorithm that is obtained by exhaustive examining the synthesis workflows and real-world data outperforms our previous work, compared from reducing the energy consumption ratio.