西安电子科技大学学报（自然科学版）2019，Vol.46Issue(1)：130-136,7.DOI:10.19665/j.issn1001-2400.2019.01.021
改进多目标进化算法的云工作流调度
Enhanced multi-objective evolutionary algorithm for workflow scheduling on the cloud platform
摘要
Abstract
The complex and dynamic pricing mechanism raises big challenges to the workflow scheduling on the cloud platform.Considering the prices of the virtualized computing and storage resources,a multiobjective optimization model is developed for the workflow running on a cloud platform.Based on the character of the target problem,a real-coding mechanism is developed for the workflow scheduling problem, so that the crossover operators in a real-coded evolutionary based optimizer can be conveniently employed and the solution repairing step in combinatorial optimization algorithms can be skipped.Following the algorithm framework of the MOEA/D,a local search strategy is designed,and a new multi-objective workflow scheduling algorithm is proposed.Experimental studies have illustrated that the proposed algorithm can obtain Pareto optimal solution sets with better coverage and uniformity than the compared algorithms,which will contribute to improving the utilization of the resources on the cloud platform.关键词
工作流调度/云计算/进化多目标优化算法/局部搜索Key words
workflow scheduling/cloud computing/evolutionary multi-objective optimization algorithm/local search分类
信息技术与安全科学引用本文复制引用
王燕..改进多目标进化算法的云工作流调度[J].西安电子科技大学学报（自然科学版）,2019,46(1):130-136,7.基金项目
国家自然科学基金(61572399) （61572399）
陕西省工业攻关项目(2017GY-076) （2017GY-076）
