基于布谷鸟搜索的虚拟机放置算法

针对虚拟机放置问题，引入了布谷鸟搜索算法。首先，将虚拟机放置方案映射为鸟巢，并按照适应度高低将其分成顶巢和底巢。其次，通过扰动函数对底巢和顶巢进行扰动。最后，通过选择、迭代得到最佳放置方案。该算法可用于云数据中心的物理机整合，使放置物理机数量最小化。通过Cloudsim进行仿真，仿真结果表明，比起重排序分组遗传算法、分组遗传算法、改进的最小加载和改进的降序首次适应算法，提出的方法不仅避免了局部最优，而且具有更高的性能优势。

Virtual machine placement algorithm based on cuckoo search

A cuckoo search algorithm was introduced for virtual machine placement.Firstly,the virtual machine placement program was mapped to the nest,and according to the level,the fitness would be divided into top and bottom nest.Secondly,the bottom nest and the top nest were disturbed by the disturbance function.Finally,by selecting,iterations got the best placement scheme.The algorithm was used for physical integration of cloud data centers,minimizing the number of physical machines placed.The algorithm is simulated by Cloudsim and the results show that the proposed method not only avoids the local optimum,but also has higher performance advantages than the reordered grouping genetic algorithm,the group genetic algorithm,the improved least load algorithm and the improved first fit decrease algorithm.