Optimising workflow execution for energy consumption and performance

Optimizing computation for energy consumption and performance requires consideration of the following three key factors: the energy consumption of the resources used; the performance of the workflow; and the time it takes to complete the computation. The increasing complexity of today's computing systems makes it essential to ensure that the resources allocated to a workload are used in the most effective and cost-efficient manner. In this paper, the importance of optimal scheduling solutions for scientific workflow computation is presented. A generic framework is proposed that takes into consideration the user constraints, performance, and factors that affect the energy consumption of different computations to develop an optimal schedule for workflow execution. The aim of the framework will be to improve the energy consumption and performance of the computation. The study also aims to motivate research in energy-efficient optimized scheduling.