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Proposing a load balancing method based on Cuckoo Optimization Algorithm for energy management in cloud computing infrastructures

机译:基于Cuckoo优化算法的云计算基础架构中能源管理的负载平衡方法

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With rapid increasing demand of cloud computing technology, energy efficiency has become highly important in cloud computing infrastructures. Cloud computing concept offers low cost and high level of availability. However, it still has some challenging problems, such as resource management and power consumption. In this concept, reducing energy consumption and maximize resource utilization, became a primary concerns of many resource management methods. In this paper, we presented an approach based on Cuckoo Optimization Algorithm (COA) to detect over-utilized hosts. Following that, we employed The Minimum Migration Time (MMT) policy to migrate Virtual Machines (VMs) from the over-utilized hosts to the other hosts. Meanwhile, the migration process should not make any more over-utilized host. Finally, we considered all the hosts, except the over-utilized ones, as the underutilized hosts. At that point, we tried to migrate all the VMs which been allocated to the underutilized hosts to the other hosts and switch them to the sleep mode. The Simulation results which generated by Cloudsim simulator, demonstrate that the proposed approach has lowest energy consumption compared to the other famous algorithms like MAD-MMT(Median Absolute Deviation- Minimum Migration Time), IQR-MMT(Interquartile Range- Minimum Migration Time), Bee-MMT(Bee colony algorithm- Minimum Migration Time), LR-MMT(local Regression-Minimum Migration Time) and non-power aware.
机译:随着云计算技术的快速增长需求,能效在云计算基础设施中非常重要。云计算概念提供低成本和高水平的可用性。但是,它仍然存在一些具有挑战性的问题,例如资源管理和功耗。在这种概念中,降低能耗和最大化资源利用率,成为许多资源管理方法的主要问题。在本文中,我们提出了一种基于Cuckoo优化算法(COA)的方法来检测过度使用的主机。在此之后,我们使用最低迁移时间(MMT)策略来将虚拟机(VM)迁移到其他主机的过度使用的主机。同时,迁移过程不应制作任何更过度使用的主机。最后,我们考虑了除了过度利用的主机之外,作为未充分利用的主人。此时,我们尝试将已分配给未充分利用主机的所有VM迁移到其他主机,并将其切换到睡眠模式。 Cloudsim模拟器产生的仿真结果表明,与MAD-MMT(中位绝对偏差 - 最小迁移时间),IQR-MMT(中位数范围 - 最小迁移时间)相比,所提出的方法具有最低能耗。 BEE-MMT(蜜蜂殖民地算法 - 最小迁移时间),LR-MMT(本地回归 - 最小迁移时间)和非功率感知。

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