基于混合算法的云计算任务调度方法研究

发布时间：2018-04-28 04:11

本文选题：混合算法 + 云计算　；参考：《现代电子技术》2016年12期

【摘要】：目前针对任务调度方法的研究中,为了降低研究难度,通常只针对某一个考量任务调度方法好坏的尺度进行研究,经常会出现优化后的方法以较高的计算成本为代价换来较短的任务完成时间,有时是得不偿失的。因此该文将任务完成时间和计算成本均作为优化的目标,对任务调度方法进行研究,平衡任务完成时间和计算成本,提高云计算的效率。该文使用遗传优化算法对上述提出的任务调度问题进行求解,并将模拟退火算法、自适应机理相结合,建立更加适合云计算任务调度求解的混合优化算法。最后,通过实验分析,以仅对任务完成时间优化和仅对计算成本优化的算法进行比较,该文研究的混合算法的云计算任务调度方法能够有效平衡任务完成时间和计算成本,有效提高云计算的效率,降低其计算成本。
[Abstract]:In the research of task scheduling methods, in order to reduce the difficulty of the research, only a certain scale of task scheduling methods is usually studied. It is common for the optimized methods to gain shorter task completion time at the cost of higher computation cost, sometimes the gain is outweighed by the loss. Therefore, the task completion time and computing cost are taken as the goal of optimization in this paper. The task scheduling method is studied to balance the task completion time and computing cost to improve the efficiency of cloud computing. In this paper, genetic optimization algorithm is used to solve the task scheduling problem mentioned above, and the simulated annealing algorithm and adaptive mechanism are combined to establish a hybrid optimization algorithm which is more suitable for the task scheduling of cloud computing. Finally, through the experimental analysis, comparing the algorithms of task completion time optimization and computation cost optimization, the hybrid algorithm of cloud computing task scheduling can effectively balance the task completion time and computing cost. Effectively improve the efficiency of cloud computing, reduce its computing costs.
【作者单位】：阿坝师范学院;
【基金】：四川省教育厅自然科学重点课题:高校数据中心建设与研究(13ZA0038);四川省教育厅自然科学重点课题:Open Flow在校园网的应用方案研究(15ZA0338)
【分类号】：TP18;TP3

【相似文献】