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Optimal Dynamic Placement of Virtual Machines in Geographically Distributed Cloud Data Centers
International Journal of Cooperative Information Systems ( IF 1.5 ) Pub Date : 2017-04-04 , DOI: 10.1142/s0218843017500010
Hana Teyeb 1, 2 , Nejib Ben Hadj-Alouane 3 , Samir Tata 4 , Ali Balma 5
Affiliation  

In geo-distributed cloud systems, a key challenge faced by cloud providers is to optimally tune and configure the underlying cloud infrastructure. An important problem in this context, deals with finding an optimal virtual machine (VM) placement, minimizing costs, while at the same time, ensuring good system performance. Moreover, due to the fluctuations of demand and traffic patterns, it is crucial to dynamically adjust the VM placement scheme over time. It should be noted that most of the existing studies, however, dealt with this problem either by ignoring its dynamic aspect or by proposing solutions that are not suitable for a geographically distributed cloud infrastructure. In this paper, exact as well as heuristic solutions based on Integer Linear programming (ILP) formulations are proposed. Our work focuses also on the problem of scheduling the VM migration by finding the best migration sequence of intercommunicating VMs that minimizes the resulting traffic on the backbone network. The proposed algorithms execute within a reasonable time frame to readjust VM placement scheme according to the perceived demand. Our aim is to use VM migration as a tool for dynamically adjusting the VM placement scheme while minimizing the network traffic generated by VM communication and migration. Finally, we demonstrate the effectiveness of our proposed algorithms by performing extensive experiments and simulation.

中文翻译:

地理分布式云数据中心中虚拟机的最佳动态放置

在地理分布式云系统中,云提供商面临的一个关键挑战是优化调整和配置底层云基础设施。在这种情况下,一个重要的问题是找到最佳的虚拟机 (VM) 放置,最大限度地降低成本,同时确保良好的系统性能。此外,由于需求和流量模式的波动,随着时间的推移动态调整 VM 放置方案至关重要。应该注意的是,现有的大多数研究都通过忽略其动态方面或提出不适合地理分布的云基础设施的解决方案来处理这个问题。在本文中,提出了基于整数线性规划 (ILP) 公式的精确和启发式解决方案。我们的工作还侧重于调度 VM 迁移的问题,方法是找到相互通信的 VM 的最佳迁移序列,从而最大限度地减少骨干网络上产生的流量。所提出的算法在合理的时间范围内执行,以根据感知的需求重新调整 VM 放置方案。我们的目标是使用虚拟机迁移作为动态调整虚拟机放置方案的工具,同时最大限度地减少虚拟机通信和迁移产生的网络流量。最后,我们通过进行广泛的实验和模拟证明了我们提出的算法的有效性。所提出的算法在合理的时间范围内执行,以根据感知的需求重新调整 VM 放置方案。我们的目标是使用虚拟机迁移作为动态调整虚拟机放置方案的工具,同时最大限度地减少虚拟机通信和迁移产生的网络流量。最后,我们通过进行广泛的实验和模拟证明了我们提出的算法的有效性。所提出的算法在合理的时间范围内执行,以根据感知的需求重新调整 VM 放置方案。我们的目标是使用虚拟机迁移作为动态调整虚拟机放置方案的工具,同时最大限度地减少虚拟机通信和迁移产生的网络流量。最后,我们通过进行广泛的实验和模拟证明了我们提出的算法的有效性。
更新日期:2017-04-04
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