云计算下的基于萤火虫-遗传算法的资源调度

如何能够最大限度发挥云计算中资源调度效率是目前研究的热点之一.首先建立云计算环境下的资源调度模型,将萤火虫算法中的个体与云计算节点资源进行对应,其次在算法中个体初始化中引入遗传算法优化初始解,对算法中的位置更新设定感觉阀值用来调节个体选择最优路径的概率;最后针对挥发因子的改进使得荧光素的值进行更新.仿真实验表明,该算法能够有效的提高云计算中的资源调度性能,缩短了任务完成的时间,提高系统整体处理能力.

Resource Scheduling Based on Firefly-Genetic Algorithm in Cloud Computing

How to give the fullest play to the efficiency of resource scheduling in cloud computing is a hot spot of current research. First of all, resource scheduling model in cloud computing is established and individuals in firefly algorithm and node resources in cloud computing are matched; secondly, the genetic algorithm is introduced into the initialization of individuals in the algorithm and sensory threshold of the updating of algorithm''s position is set to adjust the probability for individuals to choose the optimal path; finally, the volatile factor is improved to update the value of fluorescein. Simulation experiment shows that this algorithm can effectively improve the performance of resource scheduling in cloud computing, shorten the time to complete tasks and improve the system''s overall processing capacity.