Scheduling deadline-constrained scientific workflow using chemical reaction optimisation algorithm in clouds

被引：0
|
作者：
Yan C. [1 ,2 ]
Luo H. [1 ,2 ]
Hu Z. [3 ]
机构：
[1] School of Computer and Information Engineering, Henan University, Kaifeng
[2] School of Information Science and Engineering, Central South University, Changsha
[3] School of Software, Central South University, Changsha
来源：
Yan, Chaokun (ckyango@csu.edu.cn) | 2018年 / Inderscience Publishers卷 / 10期
基金：
中国国家自然科学基金; 美国国家科学基金会;
关键词：
Chemical reaction optimization; Cloud; Cost; CRO; Deadline; OED; Orthogonal experimental design; SaaS; Scientific workflow;
D O I：
10.1504/ijes.2018.095026
中图分类号：
学科分类号：
摘要：
The advent of cloud computing as a new model of service provisioning in distributed systems encourages researchers to investigate its benefits and drawbacks on executing scientific applications such as workflows. One of the most challenging problems in clouds is workflow scheduling, i.e., the problem of satisfying the QoS requirements of the users as well as minimising the cost of workflow execution. In this paper, a novel meta-heuristic method, called chemical reaction optimisation (CRO), is developed to solve deadline-constrained workflow scheduling, which tries to minimise the cost of workflow execution while meeting a user-defined deadline. A set of appropriate parameters can be obtained based on orthogonal experimental design (OED) and factor analysis. Experiments are done in two real workflow applications, and the results demonstrate the effectiveness of the proposed algorithm. © 2018 Inderscience Enterprises Ltd.
引用
收藏
页码：378 / 393
页数：15
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