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首页> 外文会议>Symposium on ICT and Energy Efficiency and Workshop on Information Theory and Security >Optimal placement of virtual machines with different placement constraints in IAAS clouds
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Optimal placement of virtual machines with different placement constraints in IAAS clouds

机译：在IAAS云中具有不同放置限制的虚拟机的最佳放置

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摘要

There has been much research activity recently in relation to the optimal placement of virtual machines (VMs) on physical servers. Usually the objective is to consolidate the VMs on servers for energy-saving purposes in a cloud environment. In this paper, we study the problem of optimizing the allocation of VMs having different placement constraints (e.g., security and anti-collocation) and characteristics (e.g., memory and disk capacity), given a set of physical hosts with known specifications, in order to achieve the objective of maximizing the cloud provider's revenue. This is an important resource allocation problem in data centers. Our approach is based on the formulation of the problem as an integer linear programming (ILP) problem. The ILP model produces an optimal placement for VMs with different placement constraints. Given a model of VM placement constraints, offered resources and required VM sets, the model devises a plan to allocate VMs to servers in a way that maximizes revenue, having due regard both to customer requirements and server capacities. The performance of the algorithms is evaluated by means of numerical experiments. Experiments suggest that this model and its associated solution strategy is practical for the offline development of VM-to-server allocation plans given a typical mix of customer demands for virtualized computing resources in small or medium data centers.
机译：最近，有关物理服务器上虚拟机（VM）的最佳放置的研究活动很多。通常，目标是在云环境中整合服务器上的VM，以实现节能目的。在本文中，我们研究了在给定一组具有已知规格的物理主机的情况下，优化具有不同放置限制（例如，安全性和防并置）和特征（例如，内存和磁盘容量）的VM分配的问题。实现最大化云提供商收入的目标。这是数据中心中重要的资源分配问题。我们的方法基于将问题表述为整数线性规划（ILP）问题。 ILP模型为具有不同放置限制的VM生成最佳放置。给定一个VM放置约束，提供的资源和所需的VM集的模型，该模型设计了一个计划，该方案以最大化收益的方式将VM分配给服务器，同时充分考虑了客户需求和服务器容量。通过数值实验评估算法的性能。实验表明，考虑到客户对小型或中型数据中心虚拟化计算资源的典型需求混合，该模型及其相关的解决方案策略对于脱机开发VM到服务器的分配计划非常实用。

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