Intelligent management of virtualized resources for database systems in cloud environment
Intelligent management of virtualized resources for database systems in cloud environment
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DOI：
10.1109/icde.2011.5767928
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发表时间：
2011-04
期刊：
影响因子：
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通讯作者：
Pengcheng Xiong;Yun Chi;Shenghuo Zhu;H. J. Moon;C. Pu;Hakan Hacıgümüş
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文献类型：
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作者：
Pengcheng Xiong;Yun Chi;Shenghuo Zhu;H. J. Moon;C. Pu;Hakan Hacıgümüş
在云计算环境中，资源在不同的客户端之间共享。在不同的客户之间智能地管理和分配资源对于系统提供商来说很重要，他们的业务模式依赖于以经济高效的方式管理基础设施资源，同时满足客户服务级别协议(SLA)。本文针对如何对共享云数据库系统中的资源进行智能管理的问题，提出了一种代价感知的资源管理系统SmartSLA。SmartSLA由两个主要组件组成：系统建模模块和资源分配决策模块。系统建模模块使用机器学习技术来学习一个模型，该模型描述了不同资源分配下每个客户的潜在利润率。在学习模型的基础上，资源分配决策模块动态调整资源分配，以实现最优收益。我们使用TPC-W基准测试来评估SmartSLA，其中工作负载特征来自真实系统。性能结果表明，SmartSLA可以成功地计算不同硬件资源分配下的预测模型，如CPU和内存，以及特定于数据库的资源，如数据库系统中的副本数。实验结果还表明，SmartSLA可以根据不同的工作负载、SLA级别、资源成本等因素提供智能服务差异化，并提高利润率。
In a cloud computing environment, resources are shared among different clients. Intelligently managing and allocating resources among various clients is important for system providers, whose business model relies on managing the infrastructure resources in a cost-effective manner while satisfying the client service level agreements (SLAs). In this paper, we address the issue of how to intelligently manage the resources in a shared cloud database system and present SmartSLA, a cost-aware resource management system. SmartSLA consists of two main components: the system modeling module and the resource allocation decision module. The system modeling module uses machine learning techniques to learn a model that describes the potential profit margins for each client under different resource allocations. Based on the learned model, the resource allocation decision module dynamically adjusts the resource allocations in order to achieve the optimum profits. We evaluate SmartSLA by using the TPC-W benchmark with workload characteristics derived from real-life systems. The performance results indicate that SmartSLA can successfully compute predictive models under different hardware resource allocations, such as CPU and memory, as well as database specific resources, such as the number of replicas in the database systems. The experimental results also show that SmartSLA can provide intelligent service differentiation according to factors such as variable workloads, SLA levels, resource costs, and deliver improved profit margins.