ITR: Proactive Self-Tuning Systems for Ubiquitous Computing

将设计、实施、部署和评估一个名为Aura的系统。AURA将利用摩尔定律可能带来的丰富计算资源，以减少对最稀缺的资源--人类注意力的需求。AURA面向涉及无线通信、可穿戴或手持计算机以及智能空间的环境。研究跨越每个系统级别：硬件、操作系统、应用程序和最终用户。AURA应用了两个广泛的概念。首先，是主动性，即一层对更高层的请求采取行动的能力。第二，是自调优：各层通过观察需求并调整性能和资源使用来匹配来适应。这两种技术都有助于降低对人类注意力的需求。这些想法将通过受控实验和一个小社区的现场使用进行评估。评估中使用的指标既包括传统的计算机系统指标，也包括以用户为中心的指标。首先，研究了Aura类系统所需的操作系统和网络能力。其次，探讨了如何捕获和利用高级用户意图来进行主动操作。第三，研究了如何使用上下文信息。这项研究的一个独特方面是它与教育的紧密结合，因为Aura原型将用于研究生水平的课程。

A system called Aura will be designed, implemented, deployed and evaluated. Aura will exploit the abundance of computing resources made possible by Moore's Law to reduce demand on the scarcest resource, human attention. Aura is targeted for environments involving wireless communication, wearable or handheld computers, and smart spaces.The research spans every system level: hardware, operating system, applications and end users. Aura applies two broad concepts. First, is proactivity, or the ability of a layer to act in anticipation of requests by a higher layer. Second, is self-tuning: layers adapt by observing the demands and adjusting performance and resource usage to match. Both techniques contribute to lowering demand on human attention. These ideas will be evaluated through controlled experiments and live use by a small community. The metrics used in evalutation include both traditional computer systems metrics plus user-centric metrics.There are three major research thrusts. First, operating system and networking capabilities required by Aura-like systems are investigated. Second, how high-level user intent can be captured and exploited for proactivity is explored. Third, how contextual information can be used is examined. A unique aspect of the research is its tight integration with education since the Aura prototype will be used in graduate-level courses.