برنامه ریزی گردش کار بی عیب مصرف انرژی و قابلیت اطمینان در سیستم های محاسباتی ناهمگن

Recent studies focus primarily on low energy consumption or execution time for task scheduling with precedence constraints in heterogeneous computing systems. In most cases, system reliability is more important than other performance metrics. In addition, energy consumption and system reliability are two conflicting objectives. A novel bi-objective genetic algorithm (BOGA) to pursue low energy consumption and high system reliability for workflow scheduling is presented in this paper. The proposed BOGA offers users more flexibility when jobs are submitted to a data center. On the basis of real-world and randomly generated application graphs, numerous experiments are conducted to evaluate the performance of the proposed algorithm. In comparison with excellent algorithms such as multi-objective heterogeneous earliest finish time (MOHEFT) and multi-objective differential evolution (MODE), BOGA performs significantly better in terms of finding the spread of compromise solutions.