NSF/CAREER: Robust Data-intensive Cluster Programming

设备复杂性和设计多样性的结合指向了系统，这些系统将由本质上和明显不同的组件构成。所需要的是一种新的设计规程，它能够解释固有的不稳定的组件行为，并促进健壮和可预测系统的设计和实现。正在一个称为Ice的集群方案编制新系统的背景下，开发强有力的应用程序开发所需的基础设施。研究沿着四个轴进行：创建完全强大的数据传输机制，探索先进的适应技术，自动化和易用性的新方法，以及发展稳健系统的理论基础。这项工作的总体目标是对如何构建可伸缩的集群系统有一个基本的理解，即使一些底层组件不能很好地工作。这种真正健壮的系统是可预测的、可靠的和可用的，尽管组件的波动和故障仍能很好地运行，并且不需要人工干预。这类系统的主要优点之一是减轻了管理负担：只需增加和充分利用新部件即可。

The combination of device complexity and design diversity point towardssystems that will be constructed from components that are both inherently andobservably heterogeneous. What is needed is a new design discipline thataccounts for inherently erratic component behavior, and facilitates thedesign and implementation of robust and predictable systems. The necessary infrastructure for robust application development is beingdeveloped within the context of a new system for cluster programming known asIce. Research proceeds along four axes: the creation of fully robustdata-transfer mechanisms, the exploration of advanced techniques foradaptation, new approaches to automation and ease-of-use, and development ofthe theoretical underpinnings of robust systems. The overall goal of this work is to develop a fundamental understanding of howto build scalable clustered systems that ``work well'', even when some of theunderlying components do not. Such truly robust systems are predictable,reliable, and available, perform well in spite of fluctuations and failures ofconstituent components, and require no human intervention. One of the mainadvantages of such systems is the reduction of the burden of administration:new components are simply added and utilized to their full capacity.