ITR: Proactive Self-Tuning Systems for Ubiquitous Computing

一个名为Aura的系统将被设计、实施、部署和评估。Aura将利用摩尔定律（Moore’s Law）带来的丰富计算资源，减少对最稀缺资源——人类注意力的需求。Aura的目标是涉及无线通信、可穿戴或手持电脑以及智能空间的环境。这项研究涵盖了每个系统级别：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，或一层在预期更高一层的请求时采取行动的能力。第二种是自调优：层通过观察需求并调整性能和资源使用来进行调整。这两种技术都有助于降低对人类注意力的需求。这些想法将通过控制实验和一个小社区的实际使用进行评估。评估中使用的度量包括传统的计算机系统度量和以用户为中心的度量。有三个主要的研究重点。首先，研究了类aura系统所需的操作系统和网络功能。其次，探讨了如何捕获和利用高级用户意图来提高主动性。第三，研究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.