Reliable and energy-efficient next-generation data centres

数据中心已成为主要的资源消耗者，年度运营预算高达数百万美元。这项工作的目标是通过解决两个主要的影响因素来更有效地运行数据中心：第一个是提供系统可靠性的挑战。 30- 40%的运营预算是由系统故障的成本和防止故障的努力构成的。第二是能源使用。典型数据中心运营预算的三分之一以上用于电力消耗。这两个问题正在成为数据中心设计的限制因素，并且随着数据中心规模的不断增长，预计未来会变得更糟。 虽然已经有很多研究致力于这些问题，但它们在很大程度上仍然没有得到解决，主要是因为传统的计算机系统研究方法（实验，仿真，分析）正在达到其极限：由于复杂性和规模，在实验室测试平台中识别和复制现实世界中的大规模系统中的问题是非常困难的。由于对数据中心中数百万个单独组件如何运行和交互的理解有限，因此很难构建逼真的模型或模拟器。我解决大规模系统设计问题的方法是首先从生产机器收集和分析大量的现场数据，以详细了解问题的性质，然后使用数据来驱动解决问题的分析和实验工作。 该提案的长期愿景是建立更可靠、更节能、更易于管理的数据中心。为了实现这一愿景，拟议的工作将集中在四个具体的近期目标上，我在最近的工作中确定了这些目标，这些目标对于解决当今数据中心效率低下的主要原因至关重要。从学术的角度来看，我们的研究将创造一个更好的理解和更现实的模型，如何大规模系统在该领域的运作，提供了一个基础，严格的研究在一个重要的领域，目前过于依赖假设和轶事。

Datacenters have turned into major resource hogs with annual operating budgets running into many millions of dollars. The goal of this work is to run datacenters more efficiently by addressing two of the main contributing factors: The first is the challenge of providing system reliability. Between 30--40\% of the operating budget is made up by the cost of system failures and efforts to protect against them. The second is energy usage. More than a third of the operating budget of a typical datacenter goes into electricity consumption. Both problems are becoming limiting factors in data center design and are predicted to get worse in the future as data centers keep growing in size. While much research has been devoted to these problems, they remain largely unsolved, mostly because traditional approaches to computer systems research (experiments, simulation, analysis) are reaching their limits: Due to the complexity and scale it is extremely difficult to identify and replicate problems in real-world large-scale systems in experimental lab testbeds. The limited understanding of how the millions of individual components in data centers operate and interact makes it very hard to build realistic models or simulators. My approach to addressing problems in large-scale system design is to first collect and analyze large amounts of field data from production machines to derive a detailed understanding of the nature of a problem and then use the data to drive the analytical and experimental work for solving a problem. The long-term vision of this proposal are data centers that are more reliable, more energy-efficient and easier to manage. To achieve this vision the proposed work will focus on four specific near-term goals that I identified in recent work as crucial to combat major sources of inefficiencies in today's data centres. From an academic point of view, our research will create a better understanding and more realistic models of how large-scale systems operate in the field, providing a foundation for rigorous research in an important area that is currently relying too much on assumptions and anecdotes.