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Bayesian Networks-Based Selection Algorithm for Virtual Machine to Be Migrated

机译:基于贝叶斯网络的虚拟机迁移选择算法

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摘要

In cloud data centers, virtual machine (VM) consolidation is one of the challenge topics. In which, the selection of VMs to be migrated is one of the key issues in the process of VM consolidation. In this paper, under consideration of the dynamical uncertain environment, a Bayesian networks-based estimation model was constructed. Because excessive VM migrations influence the Quality of Service (QoS) of data center, the model aims at estimating the migration probability of VMs and calculating the potential total number of migrations occurred in physical hosts. Based on the proposed model, a Bayesian networks-based selection algorithm (BN-SA) for VMs to be migrated was proposed. The BN-SA adaptively adjusts the overloaded threshold and selects VMs which have relatively short migration time and big impact on potential migrations of host in the phase of reallocating VMs. The experimental results show that BN-SA algorithm has a promising performance.
机译:在云数据中心中,虚拟机(VM)整合是挑战性主题之一。其中,要迁移的VM的选择是VM整合过程中的关键问题之一。本文在考虑动态不确定性环境的基础上,构建了基于贝叶斯网络的估计模型。由于过多的VM迁移会影响数据中心的服务质量(QoS),因此该模型旨在估算VM的迁移概率,并计算物理主机中可能发生的迁移总数。在此模型的基础上,提出了一种基于贝叶斯网络的虚拟机迁移算法。 BN-SA自适应地调整过载阈值,选择迁移时间相对较短,在重新分配虚拟机阶段对主机潜在迁移影响较大的虚拟机。实验结果表明,BN-SA算法具有良好的性能。

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