Computing devices and applications are now used beyond the desktop, in diverse environments, and this trend toward ubiquitous computing is accelerating. One challenge that remains in this emerging research field is the ability to enhance the behavior of any application by informing it of the context of its use. By context, we refer to any information that characterizes a situation related to the interaction between humans, applications, and the surrounding environment. Context-aware applications promise richer and easier interaction, but the current state of research in this field is still far removed from that vision. This is due to 3 main problems: (a) the notion of context is still ill defined, (b) there is a lack of conceptual models and methods to help drive the design of context-aware applications, and (c) no tools are available to jump-start the development of context-aware applications. In this anchor article, we address these 3 problems in turn. We first define context, identify categories of contextual information, and characterize context-aware application behavior. Though the full impact of context-aware computing requires understanding very subtle and high-level notions of context, we are focusing our efforts on the pieces of context that can be inferred automatically from sensors in a physical environment. We then present a conceptual framework that separates the acquisition and representation of context from the delivery and reaction to context by a context-aware application. We have built a toolkit, the Context Toolkit, that instantiates this conceptual framework and supports the rapid development of a rich space of context-aware applications. We illustrate the usefulness of the conceptual framework by describing a number of context-aware applications that have been prototyped using the Context Toolkit. We also demonstrate how such a framework can support the investigation of important research challenges in the area of context-aware computing.

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A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications

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.

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Providing architectural support for building context-aware applications

The EasyLiving project is concerned with development of an architecture and technologies for intelligent environments which allow the dynamic aggregation of diverse I/O devices into a single coherent user experience. Components of such a system include middleware (to facilitate distributed computing), world modelling (to provide location-based context), perception (to collect information about world state), and service description (to support decomposition of device control, internal logic, and user interface). This paper describes the current research in each of these areas, highlighting some common requirements for any intelligent environment.

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EasyLiving: Technologies for Intelligent Environments

Recommender systems using collaborative filtering are a popular technique for reducing information overload and finding products to purchase. One limitation of current recommenders is that they are not portable. They can only run on large computers connected to the Internet. A second limitation is that they require the user to trust the owner of the recommender with personal preference data. Personal recommenders hold the promise of delivering high quality recommendations on palmtop computers, even when disconnected from the Internet. Further, they can protect the user's privacy by storing personal information locally, or by sharing it in encrypted form. In this article we present the new PocketLens collaborative filtering algorithm along with five peer-to-peer architectures for finding neighbors. We evaluate the architectures and algorithms in a series of offline experiments. These experiments show that Pocketlens can run on connected servers, on usually connected workstations, or on occasionally connected portable devices, and produce recommendations that are as good as the best published algorithms to date.

PocketLens: Toward a personal recommender system

A just-in-time information retrieval agent (JITIR agent) is software that proactively retrieves and presents information based on a person's local context in an easily accessible yet nonintrusive manner. This paper describes three implemented JITIR agents: the Remembrance Agent, Margin Notes, and Jimminy. Theory and design lessons learned from these implementations are presented, drawing from behavioral psychology, information retrieval, and interface design. They are followed by evaluations and experimental results. The key lesson is that users of JITIR agents are not merely more efficient at retrieving information, but actually retrieve and use more information than they would with traditional search engines.

Just-in-time information retrieval agents

Hive is a distributed agent platform, a decentralized system for building applications by networking local system resources. This paper presents the architecture of Hive, concentrating on the idea of an "ecology of distributed agents" and its implementation in a practical Java-based system. Hive provides ad-hoc agent interaction, ontologies of agent capabilities, mobile agents and a graphical interface to the distributed system. We are applying Hive to the problems of networking "Things That Think" (TTT), putting computation and communication in everyday places, such as your shoes, your kitchen or your own body. TTT shares the challenges and potentials of ubiquitous computing and embedded network applications. We have found that the flexibility of a distributed agent architecture is well suited for this application domain, enabling us to easily build applications and to reconfigure our systems on-the-fly. Hive enables us to make our environment and network more alive.

Hive: distributed agents for networking things

The authors present Hive, a decentralized system for building applications by networking local system resources. They are applying it to the problems of networking "Things That Think," embedding computation and communication in everyday objects and appliances.

P. Maes

Papers

Hive: distributed agents for networking things

Hive: distributed agents for networking things