Chorus: A Resource Management Framework for Cost Effective Quality of Service in Cloud Environments

随着互联网上经济和协作交换的全部潜力变得明显，基于Web的应用程序和用户需求呈指数级增长。许多服务现在依赖于称为云环境的共享基础设施，目前由大型服务托管提供商维护。不幸的是，在幕后，云提供商面临着巨额的管理成本，这些成本消耗了他们高达88%的预算，主要是由于服务器管理、电力和冷却运营成本。这限制了再投资、研究和开发，对该行业的效率造成了障碍，也是由于主要能源消耗而造成的环境问题。而且，对灵活、无处不在、可定制的云接入的需求只会以陡峭的速度增长。 为了解决这些问题，我们建议设计、实现和部署一个新的云资源管理框架Chorus，旨在用作跨学科研究的协作环境。Chorus是一个轻量级、可移植的虚拟化解决方案，包括用于性能建模、异常诊断和高效资源分配的算法、高级语言和工具。我们的技术将允许对云服务托管环境中的资源进行自动检测并将应用程序干扰降至最低，自动节能，以及系统管理员针对容量规划和异常诊断进行灵活的假设查询。通过这些新提出的技术，我们的系统Chorus将自动提供性能优化，以提高所有托管应用程序的端到端服务质量合规性，并降低托管提供商的成本。我们将通过运行各种实际工作负载来演示我们实验室内云环境的功能，从模仿Amazon.com和eBay.com的工作负载的常见电子商务工作负载组合，到功能性MRI医学图像处理应用程序。

As the full potential of economic and collaborative exchange over the Internet has become clear, Web-based applications and user demand have increased exponentially. Many services now rely on shared infrastructures, called Cloud environments, currently maintained by large service hosting providers. Unfortunately, behind the scenes, Cloud providers are strapped with large administrator costs, costs which consume up to 88% of their budgets, mainly due to server management, power and cooling operational costs. This creates an impediment on the efficiency of this industry, by limiting reinvestment, research and development, and also an environmental problem due to major energy consumption. And demand for flexible, ubiquitous, customizable Cloud access is only going to increase at a steep rate. To address these problems, we propose to design, implement and deploy a novel Cloud resource management framework, Chorus, intended for use as a collaborative environment for interdisciplinary research. Chorus is a lightweight and portable virtualization solution including algorithms, high level languages and tools for performance modeling, anomaly diagnosis and efficient resource allocation. Our techniques will allow for automatic detection and minimization of application interference for resources in Cloud service hosting environments, and automatic power savings, as well as for flexible what-if inquiry for capacity planning and anomaly diagnosis by the system administrator. By these novel proposed techniques, our system, Chorus, will automatically provide performance optimizations towards improving end-to-end Quality of Service compliance for all hosted applications as well as cost reductions for the hosting provider. We will demonstrate the capabilities of our in-lab Cloud environment by running a variety of realistic workloads, ranging from common e-commerce workload mixes modeled after the workloads of the Amazon.com and EBay.com, to functional MRI medical image processing applications.