.png){kind=icon}
返回
Towards decomposition based multi-objective workflow scheduling for big data processing in clouds
.png){kind=icon}
PRE
AI
DOI：10.1007/s10586-020-03208-w.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A workflow is a group of tasks that are processed in a particular order to complete an application. Also, it is a popular paradigm used to model complex big-data applications. Executing complex applications in a distributed system such as cloud or cluster implicates optimization of several conflicting objectives such as monetary cost, energy consumption, total execution time of the application (makespan). Regardless of this trend, most of the workflow scheduling approaches focused on single or bi-objective optimization problem. In this paper, we considered the problem of scheduling workflows in a cloud environment as a multi-objective optimization problem, and hence proposed a multi-objective workflow-scheduling algorithm based on decomposition. The proposed algorithm is capable of finding optimal solutions with a single run. Our evaluation results show that, by a single run, the proposed approach manages to obtain the Pareto Front solutions which are at least as good as schedules produced by running a single-objective scheduling algorithm with constraints for multiple times.
Keyword:
Multi-objective optimization
Workflow scheduling
Cloud computing
Decomposition approach
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.1
论文数:
5.0K
被引数:
7.5K
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容