Using simulation to improve workflow scheduling in heterogeneous computing systems

Abstract

Workflows is an important class of parallel applications that consist of many tasks with logical or data dependencies. A multitude of scheduling algorithms have been proposed to optimize the workflow execution in heterogeneous computing systems. However, in order to be efficiently applied in practice, these algorithms require accurate estimates of task execution and communication times. In this paper two modifications of the well-known HEFT algorithm are investigated that use simulation instead of simple analytical models in order to better estimate data transfer times. The results of experimental study show that the proposed approach can improve makespan for data-intensive workflows with high parallelism and communication-to-computation ratio.