基于改进的花授粉算法的虚拟机分配策略

Improved Flower Pollination Algorithm Based Virtual Machine Allocation Approach in Cloud Data Centers

构造绿色云数据中心的两个主要目标是低能量消耗与物理资源利用效率的充分利用,为此需要采用虚拟机分配策略来完成优化。本文提出了基于改进花授粉算法的虚拟机分配策略(Flower pollination algorithm based virtual machine allocation,FPA-VMA)。FPA?VMA中一朵花或一个配子就对应于虚拟机映射到物理主机分配优化问题中的一个解;并且描述了云数据中心云客户端的资源请求模型和多维物理资源的能量消耗模型。FPA?VMA在花授粉的动态切换概率阶段的策略可以平衡全局最优解搜索和局部最优解搜索之间的切换,同时改善资源分配的全局收敛能力。真实的虚拟机数据的访问测试结果标明:FPA?VMA比常见的虚拟机分配优化策略有更低的能量消耗和更高的物理资源利用效率。

For a cloud data center,minimizing resource wastage and increasing resource utility efficiency are two important aims.So an efficient virtual machine allocation strategy is necessary.A flower pollination algorithm based virtual machine allocation(FPA-VMA)approach is proposed.In FPA-VMA,the plant has only one flower,and each flower produces only one pollen gamete.The flower and pollen gamete are similar to the virtual machine and physical machine in cloud data center.The cloud client resource requesting model and the multi-dimensional resource energy consumption model are also analyzed and described.FPA-VMA uses a strategy which is called dynamic switching probability(DSP).DSP finds a near optimal solution quickly and balances the exploration of the global search and exploitation of the local search,thus improving the global convergence of FPA-VMA.Experimental results on the real virtual machine workloads show that FPA-VMA has better performance in resource wastage and energy consumption compared with previous VMA strategies.