Using Layered Bottlenecks for Virtual Machine Provisioning in the Clouds

Yasir Shoaib, O. Das
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引用次数: 6

Abstract

Meeting the QoS objectives of fluctuating web workload requires techniques built on performance models, controller algorithms, monitors, etc. To meet the demands, we propose a controller algorithm using performance models that addresses the dynamic provisioning problem of multi-tier web applications in the cloud computing domain through addition of resources. The proposed algorithm aims to attain response time objectives by identifying "layered bottlenecks" and on this basis adding virtual machines (VM) and virtual CPUs, while keeping a check on limits such as spare VMs, processors-per-VM and replicas-per-VM. Here, Layered Queueing Network (LQN) performance models are used, alongside jLQNInterface, a tool developed in Java that allows solving, analyzing, and manipulating LQN models through the implemented API. The algorithm has been implemented using the tool and its applicability is demonstrated through a case study. By comparing two cases, it is shown that the proposed algorithm by using layered bottlenecks results in a model that satisfies the objectives with fewer resources.
在云中的虚拟机配置中使用分层瓶颈
满足波动的web工作负载的QoS目标需要建立在性能模型、控制器算法、监视器等基础上的技术。为了满足需求,我们提出了一种使用性能模型的控制器算法,该算法通过添加资源来解决云计算领域多层web应用程序的动态供应问题。所提出的算法旨在通过识别“分层瓶颈”并在此基础上添加虚拟机(VM)和虚拟cpu来达到响应时间目标,同时检查诸如备用虚拟机,每个虚拟机的处理器和每个虚拟机的副本等限制。这里使用了分层队列网络(LQN)性能模型,以及jLQNInterface, jLQNInterface是一种用Java开发的工具,允许通过实现的API解决、分析和操作LQN模型。利用该工具实现了该算法,并通过实例验证了该算法的适用性。通过两种情况的比较,表明采用分层瓶颈的算法能以较少的资源得到满足目标的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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