DMS Algorithm in the Application of the Map/Reduce Tasks Schedule
The whole efficiency of traditional task scheduling algorithms is low under the cloud environment, In order to improve the whole efficiency of the task scheduling, this article based on Map/Reduce presents a Difference Matrix Scheduling tasks schedule algorithm based on processing time. Firstly, pre...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2019-02-01
|
| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1639 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The whole efficiency of traditional task scheduling algorithms is low under the cloud environment, In order to improve the whole efficiency of the task scheduling, this article based on Map/Reduce presents a Difference Matrix Scheduling tasks schedule algorithm based on processing time. Firstly, pretreatment of complex tasks, the complex tasks is converted to Directed Acyclic Graph figure, the tasks are topological sorted in an optimal manner according to the size of the task dependencies, and the work node is accordance with the sort to processing the complex tasks; Secondly, using the ratio of predictive time that node process tasks to node process capacity as a subtask in each node time quantitative modeling, then establish the task and the metric matrix of process time, according the Difference Matrix Scheduling to processing the matrix, and obtain the optimal scheme of task assignment. Finally, the experiment evaluates the Difference Matrix Scheduling ,fair scheduling algorithm, genetic algorithm in the task scheduling and resource utilization efficiency angles. The results show that the algorithm can significantly improve the overall efficiency of complex task scheduling and make full use of the capacity of the compute nodes to improve the Map / Reduce scheduling efficiency. |
|---|---|
| ISSN: | 1007-2683 |