Order@Cloud:基于多目标位置排名的虚拟机组织框架

G. Geronimo, Rafael Brundo Uriarte, Carlos Becker Westphall
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引用次数: 5

摘要

本文介绍了一个名为Order@Cloud的灵活可扩展框架的实现和测试,该框架可以改善云中的虚拟机位置。它接收云上的新虚拟机,并根据环境的多目标重新定位它们的位置来组织它们。这些目标由规则、限定词和成本表示,可以很容易地添加、扩展和确定优先级。基于进化和贪婪搜索,Order@Cloud在理论上保证采用更好的位置集。更具体地说,它寻求非支配的解决方案(帕累托集),并考虑场景的实现成本和收益对它们进行比较。与现有的解决方案相比,我们的框架被设计成与目标无关且易于扩展的,这使得实现新的和通用的优先级元素成为可能。为了了解我们的解决方案的适用性和性能,我们使用真实的云环境进行了实验,并讨论了其性能、灵活性和最优性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Order@Cloud: A VM organisation framework based on multi-objectives placement ranking
This paper presents the implementation and tests of a flexible and extensible framework, named Order@Cloud, that improves the Virtual Machine placements of a Cloud. It receives new VMs on the Cloud and organises them by relocating their placements based on the Multiple-Objectives of the environment. These Objectives are represented by Rules, Qualifiers and Costs, which can be easily added, extended and prioritised. Based on Evolutionary and Greedy Searches, Order@Cloud theoretically guarantees the adoption of a better set of Placements. More specifically, it seeks the non-dominated solutions (Pareto Set) and compares them considering the implementation cost of the scenario and its benefits. In contrast to existing solutions, that address specific objectives, our framework was devised to be objective-agnostic and easily extensible, which enables the implementation of new and generic prioritised elements. To understand the applicability and performance of our solution we conducted experiments using a real Cloud environment and discuss its performance, flexibility and optimality.
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