摘要
针对云计算环境下的独立实时任务的节能调度问题进行了研究,设计了一种基于松弛时间的任务调度算法,该算法由实时任务的分配、虚拟机资源的动态扩展以及虚拟机的动态整合3个部分组成,通过计算任务的松弛时间保证任务在截止期限内完成,保证任务的时效性.同时提出了一种基于多阈值的虚拟机整合策略,以平衡系统负载并降低系统完成任务集合的能耗.实验表明,与其他算法相比,该算法在保证了任务能够按时完成的基础上,有效降低了系统的整体能耗.
In this paper, we study the problem of energy-efficient scheduling for real-time tasks. A task scheduling algo-rithm based on the slack time of tasks is designed. Three components of the algorithm are the distribution of real-time tasks, dynamically expanding virtual machine resource and integration of virtual machine resource. By computing the slack time of tasks, tasks can be completed within the deadline to ensure the timeliness of the task. With a multi-threshold- based virtual machine integration strategy, the system load is balanced and energy consumption of the system to complete the task set is reduced. Experiments show that , comparing with two other scheduling algorithms, the algorithm in this paper ensures that tasks can be completed on time, and energy consumption of the system can be efficiently reduced.
出处
《南京师范大学学报（工程技术版）》
CAS
2016年第3期81-87,共7页
Journal of Nanjing Normal University(Engineering and Technology Edition)
基金
江苏省自然科学基金(BK20161338)
江苏省"六大人才高峰"高层次人才项目(2012-WLW-024)
江苏省产学研联合创新资金(前瞻性联合研究)项目(BY2013063-10)
扬州大学研究生创新项目(CXLX_1415)
扬州市"绿扬金凤计划"创业创新领军人才项目(2013-50)
关键词
云数据中心
实时任务
任务松弛时间
节能调度
cloud data center, real-time tasks, slack time of tasks, energy-efficient scheduling
