摘要
针对云计算下的资源调度的问题,提出将蚁群算法的个体与云计算中的可行性资源调度进行对应,首先对云计算资源调度进行描述,其次针对蚁群算法的路径选择引入了平衡因子,对信息素进行了局部研究和全局研究,将蚁群个体引入到膜计算中,通过膜内运算和膜间运算,提高了算法的局部和全局收敛的能力,最后在云计算资源分配中,引入匹配表概念,将云计算任务和资源进行匹配,融合后的算法提高了算法的整体性能;仿真实验说明在网络消耗,成本消耗,能量消耗上有了明显的降低,提高了资源分配效率。
Aiming at the issue of resource scheduling in cloud computing, this paper proposes to correspond individuals in ant colony algorithm with feasibility resource scheduling in cloud computing. Firstly, it describes resource scheduling in cloud computing and then aiming at the path choice of ant colony, balancing factor is introduced for global research into pheromone, and individual ants are introduced into the calculation of membrane. The membrane computing and membrane operations have improved the ability of local and global convergence. Finally, in resource allocation of cloud computing, the concept of matching table is introduced to match tasks and resources in cloud computing. The integrated algorithm has improved the entire performance of the algorithm, and simulation platform experiment shows that it has reduce the network consumption, cost consumption and energy consumption as well as the resource allocation efficiency.
出处
《计算机测量与控制》
2017年第1期127-130,共4页
Computer Measurement &Control
基金
国家自然基金项目(61303227)
关键词
蚁群算法
膜计算
平衡因子
信息素
匹配表
ant colony algorithm
membrane computing
balancing factor
pheromone
matching table