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Network-aware virtual machine placement in cloud data centers with multiple traffic-intensive components

机译:具有多个流量密集型组件的可将网络感知的虚拟机放置在云数据中心中

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摘要

Following a shift from computing as a purchasable product to computing as a deliverable service to consumers over the Internet, cloud computing has emerged as a novel paradigm with an unprecedented success in turning utility computing into a reality. Like any emerging technology, with its advent, it also brought new challenges to be addressed. This work studies network and traffic aware virtual machine (VM) placement in a special cloud computing scenario from a provider's perspective, where certain infrastructure components have a predisposition to be the endpoints of a large number of intensive flows whose other endpoints are VMs located in physical machines (PMs). In the scenarios of interest, the performance of any VM is strictly dependent on the infrastructure's ability to meet their intensive traffic demands. We first introduce and attempt to maximize the total value of a metric named "satisfaction" that reflects the performance of a VM when placed on a particular PM. The problem of finding a perfect assignment for a set of given VMs is NP-hard and there is no polynomial time algorithm that can yield optimal solutions for large problems. Therefore, we introduce several off-line heuristic-based algorithms that yield nearly optimal solutions given the communication pattern and flow demand profiles of subject VMs. With extensive simulation experiments we evaluate and compare the effectiveness of our proposed algorithms against each other and also against naïve approaches. © 2015 Elsevier B.V.All rights reserved.
机译:从将计算作为可购买产品转变为通过互联网向消费者提供可交付服务的计算之后,云计算已成为一种新颖的范例,在将公用计算变为现实方面取得了空前的成功。像任何新兴技术一样,它的出现也带来了新的挑战需要解决。这项工作从提供商的角度研究了在特殊的云计算场景中的网络和流量感知虚拟机(VM)的放置情况,其中某些基础架构组件容易成为大量密集流的端点,而其他端点是位于物理位置的VM机器(PM)。在感兴趣的场景中,任何VM的性能都严格取决于基础架构满足其密集流量需求的能力。我们首先介绍并尝试最大程度地提高名为“满意度”的指标的总价值,该指标反映了放置在特定PM上的VM的性能。为一组给定的虚拟机找到一个完美分配的问题是NP难的,并且没有多项式时间算法可以为大问题提供最优解。因此,我们介绍了几种基于脱机启发式的算法,这些算法根据主题VM的通信模式和流量需求配置文件,产生了几乎最佳的解决方案。通过广泛的仿真实验,我们评估并比较了我们提出的算法彼此之间以及与幼稚方法之间的有效性。 ©2015 Elsevier B.V.保留所有权利。

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