摘要
为了保证各资源之间的任务平衡,提出一种遗传算法和蚁群算法相结合的云计算环境下资源调度优化方法。该方法首先设计云计算环境下资源调度的约束条件,并建立资源调度的数学模型,然后采用遗传算法的全局搜索能力对数学模型进行求解,得到云计算环境下资源调度的可行方案集合,并采用蚁群算法对资源调度的可行方案进行局部搜索求解,找到云计算环境下资源调度的最佳方案,最后在Cloud Sin平台进行了模拟实验。结果表明,本文算法可以有效保证云计算资源之间的负载均衡,加快了任务完成时间,并且性能要优于遗传算法和蚁群算法。
In order to ensure the balance between the resources,this paper proposes a resource scheduling and optimization method in cloud computing environment by combination genetic algorithm with ant colony algorithm. Firstly,design constraints of cloud computing resource scheduling environment,and establish the mathematical model. Then,the mathematical model is solved by genetic algorithm which has global searching ability to obtain feasible scheme of resource scheduling that ant colony algorithm is used to search and solve feasible scheme to find the best solution for resource scheduling. Finally the simulation experiment was carried out on Cloud Sin platform. The results show that the load balance between resources in cloud computing environment can be guaranteed by the proposed method,and the performance is better than genetic algorithm and ant colony algorithm.
出处
《激光杂志》
北大核心
2016年第6期115-118,共4页
Laser Journal
基金
国家自然科学基金(61379026)
关键词
云计算
资源调度
负载均衡
遗传算法
蚁群算法
cloud computing
resource scheduling
load balancing
genetic algorithm
ant colony algorithm
