计算机应用与软件2024，Vol.41Issue(1)：278-284,7.DOI:10.3969/j.issn.1000-386x.2024.01.040
面向云平台的免疫多目标优化调度算法
IMMUNE MULTI-OBJECTIVE OPTIMIZATION SCHEDULING ALGORITHM FOR CLOUD PLATFORM
摘要
Abstract
In the cloud environment,there are various characteristics among tasks.Due to the changes and uncertainties in the traditional resource allocation mechanism,load imbalance is easy to cause scheduling constraints,and task delay constraints also reduce the utilization of task scheduling policies.To solve this problem,a cloud-oriented platform immune multi-objective optimization scheduling algorithm is proposed.Pareto dominance relation was used to design the mathematical model of cloud computing task scheduling problem.After population initialization,Pareto optimal solution,calculation of crowding distance,clone selection,recombination and variation,the diversity of population was maintained and the global optimization of scheduling was realized.Compared with the traditional algorithm,the experiments show that the proposed algorithm has a wider search range,better search breadth of solutions,and can balance the task execution time and cost effectively,and improve user satisfaction.关键词
云平台/人工免疫/多目标/任务调度算法Key words
Cloud platform/Artificial immunity/Multi-objective/Task scheduling algorithm分类
信息技术与安全科学引用本文复制引用
李颖,邵清,王清雲,周子航,夏凤阳..面向云平台的免疫多目标优化调度算法[J].计算机应用与软件,2024,41(1):278-284,7.基金项目
国家重点研发计划项目(2018YFB1700902). （2018YFB1700902）
