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A Cloud Resource Allocation Method Supporting Sudden and Urgent Demands

机译:一种支持突发需求的云资源分配方法

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In most emergent circumstances, the information resources are not enough or not provided timely, which needs a comprehensive information technique to support rapid and sufficient resource provision. Cloud computing can promote rapid resource allocation, which provides a practical technical support for emergencies. Its key problem is how to guarantee the timeliness and optimization of resource allocation. This paper proposes a cloud resource allocation method supporting sudden and urgent demands, which can allocate various resources timely and optimally for urgent resource demands. This method rebuilds the new priorities of resource allocation in order to allocate resources earlier for urgent virtual machine requests. And a multi-objective optimization mathematical model is established, which sets the minimum performance match distance between virtual machines and physical machines and the minimum number of physical machines as the goals of resource allocation. Then, a multiple-objective optimization algorithm is used to solve this model. We conduct an experiment to exhibit our method. The initial experimental results show that our method has a certain advantage in reducing the number of the used physical machines and improving the resource utilization.
机译:在大多数紧急情况下,信息资源不足或没有及时提供,这需要一种全面的信息技术来支持快速而充足的资源提供。云计算可以促进资源的快速分配,这为紧急情况提供了实用的技术支持。其关键问题是如何保证资源配置的及时性和优化性。本文提出了一种支持突发事件和紧急需求的云资源分配方法,该方法可以针对紧急资源需求及时,优化地分配各种资源。此方法重建资源分配的新优先级,以便更早地为紧急虚拟机请求分配资源。建立了多目标优化数学模型,该模型将虚拟机与物理机之间的最小性能匹配距离和最小物理机数量作为资源分配的目标。然后,采用多目标优化算法求解该模型。我们进行了实验以展示我们的方法。初步的实验结果表明,我们的方法在减少使用的物理机数量和提高资源利用率方面具有一定的优势。

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