文化框架下多群智能优化算法的云作业调度

作业调度是一种云计算核心技术,为了获得更优的云计算作业调度方案,提出一种文化框架下多群智能优化算法的云作业调度方法。首先构建云作业调度问题的数学模型,然后借助文化算法模型,粒子群算法组成信仰空间,人工鱼群算法组成群体空间,两者之间并行演化,相互促进,对云计算作业调度数学模型进行求解,最后通过仿真实验测试算法的性能。结果表明,本文加快了算法的收敛速度,获得了更优的云计算作业调度方案,大幅度缩短少云计算作业完成时间,具有一定的实用价值。

Job Scheduling in Cloud Computing Based on Multi-swarm Optimization Algorithm With Cultural Algorithm

Job scheduling is the core technology of cloud computing, in order to obtain good scheduling results, a new job scheduling method in cloud computing based on multi-swarm optimization algorithm with cultural algorithm is proposed in this paper. Firstly, The mathematical model is constructed for cloud scheduling problem, and then with the help of cultural algorithm model, particle swarm algorithm consists of the belief space while artificial fish swarm algorithm consists of group space, their parallel evolution and promote each other to solve the job scheduling mathematical model, finally, the simulation experiment is carried out to test the performance of the algorithm. The results show that, the proposed algorithm has fastened convergence speed and can obtain a better job scheduling scheme of cloud computing, and greatly shorten the work time, so it has a certain practical value.