摘要
为了提升异构分布式环境下处理具有依赖关系的任务的性能,提出一种基于关键任务和处理器选择参数的启发式任务调度算法(HCNPSV)。该算法结合表调度和任务复制调度的思想,改进了关键任务的计算方法,并按照是否为关键任务、上行权重值递减、关联任务数递增的顺序获得调度序列,资源选择阶段综合考虑了任务的最早完成时间和到出口节点的最短距离,最后将任务调度到处理器选择参数最小的资源上执行。实验结果表明,HCNPSV有效地提高了系统的调度性能。
This paper proposes HCNPSV algorithm based on critical task and processor selection value to improve theperformance of processing dependent tasks in heterogeneous and distributed environment.The algorithm combines listscheduling and task duplication scheduling,improves the method of calculating critical tasks,gives highest priority to criticaltasks and decrement of upword rank and increment of number of related tasks by the order of sort.Besides this paperestablishes parameter based on earliest finish time and least distance exit time of the tasks to select processors,finallytasks assign to the value minimum resources to perform.Experiments show that HCNPSV scheduling enhances the performance.
作者
贾丽云
张向利
张红梅
JIA Liyun;ZHANG Xiangli;ZHANG Hongmei(Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China)
出处
《计算机工程与应用》
CSCD
北大核心
2017年第12期63-69,共7页
Computer Engineering and Applications
基金
国家自然科学基金(No.61363031
No.61462007
No.61461010)
广西高校云计算与复杂系统重点实验室研究课题(No.14101)
关键词
分布式系统
静态任务调度
有向无环图
关键任务
任务复制
distributed systems
static task scheduling
Directed Acyclic Graph(DAG)
critical task
task duplication