基于改进的蝙蝠算法在云计算中的资源分配

云计算中的资源分配一直都是研究的重点, 提出了一种基于改进的蝙蝠算法的云计算资源分配方法. 在蝙蝠算法中引入差分遗传算法, 通过变异, 交叉和选择等操作避免个体陷入局部最优, 以及过早产生最优解的可能,改进后的蝙蝠算法能够有效的提高收敛速度和精度. 仿真实验表明, 本文算法不但有效提高了算法性能, 还优化了云计算系统中的资源调度能力, 提高了云计算资源的利用率.

Resources Allocation in Cloud Computing Based on Improved Bat Algorithm

Resource allocation in cloud computing has always been the focus of research, and in this paper, a resource allocation in cloud computing based on improved bat algorithm has been proposed. Differential genetic algorithm is introduced into bat algorithm and mutation, crossover and selection, etc. are employed to avoid individuals from falling into local optimum, and premature of the optimal solution. The improved bat algorithm can effectively improve the convergence speed and precision of the algorithm. Simulation experiments have shown that algorithm in this paper can not only greatly improve performance of the algorithm, but also optimize the resource scheduling capability in cloud computing system and improve utilization rate of resources in could computing.