Ph. D. Thesis Dissertation, College of Computing, Georgia Tech.

Providing Architectural Support for Building Context-Aware Applications
Anind K. Dey

Traditional interactive applications are limited to using only the input that users explicitly provide. As users move away from traditional desktop computing environments and move towards mobile and ubiquitous computing environments, there is a greater need for applications to leverage from implicit information, or context. These types of environments are rich in context, with users and devices moving around and computational services becoming available or disappearing over time. This information is usually not available to applications but can be useful in adapting the way in which it performs its services and in changing the available services. Applications that use context are known as context-aware applications.

This research in context-aware computing has focused on the development of a software architecture to support the building of context-aware applications. While developers have been able to build context-aware applications, they have been limited to using a small variety of sensors that provide only simple context such as identity and location. This dissertation presents a set of requirements and component abstractions for a conceptual supporting framework. The framework along with an identified design process makes it easier to acquire and deliver context to applications, and in turn, build more complex context-aware applications.

In addition, an implementation of the framework called the Context Toolkit is discussed, along with a number of context-aware applications that have been built with it. The applications illustrate how the toolkit is used in practice and allows an exploration of the design space of context-aware computing. This dissertation also shows how the Context Toolkit has been used as a research testbed, supporting the investigation of difficult problems in context-aware computing such as the building of high-level programming abstractions, dealing with ambiguous or inaccurate context data and controlling access to personal context.