Jadwiga Indulska

A survey of context modelling and reasoning techniques

Development of context-aware applications is inherently complex. These applications adapt to changing context information: physical context, computational context, and user context/tasks. Context information is gathered from a variety of sources that differ in the quality of information they produce and that are often failure prone. The pervasive computing community increasingly understands that developing context-aware applications should be supported by adequate context information modelling and reasoning techniques. These techniques reduce the complexity of context-aware applications and improve their maintainability and evolvability. In this paper we discuss the requirements that context modelling and reasoning techniques should meet, including the modelling of a variety of context information types and their relationships, of situations as abstractions of context information facts, of histories of context information, and of uncertainty of context information. This discussion is followed by a description and comparison of current context modelling and reasoning techniques.

Modeling Context Information in Pervasive Computing Systems

As computing becomes more pervasive, the nature of applications must change accordingly. In particular, applications must become more flexible in order to respond to highly dynamic computing environments, and more autonomous, to reflect the growing ratio of applications to users and the corresponding decline in the attention a user can devote to each. That is, applications must become more context-aware. To facilitate the programming of such applications, infrastructure is required to gather, manage, and disseminate context information to applications. This paper is concerned with the development of appropriate context modeling concepts for pervasive computing, which can form the basis for such a context management infrastructure. This model overcomes problems associated with previous context models, including their lack of formality and generality, and also tackles issues such as wide variations in information quality, the existence of complex relationships amongst context information and temporal aspects of context.

Developing context-aware pervasive computing applications: Models and approach

There is growing interest in the use of context-awareness as a technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of users. However, context-awareness introduces a variety of software engineering challenges. In this paper, we address these challenges by proposing a set of conceptual models designed to support the software engineering process, including context modelling techniques, a preference model for representing context-dependent requirements, and two programming models. We also present a software infrastructure and software engineering process that can be used in conjunction with our models. Finally, we discuss a case study that demonstrates the strengths of our models and software engineering approach with respect to a set of software quality metrics.

A software engineering framework for context-aware pervasive computing

There is growing interest in the use of context-awareness as a technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of users. However, context-awareness introduces various software engineering challenges, as well as privacy and usability concerns. In this paper, we present a conceptual framework and software infrastructure that together address known software engineering challenges, and enable further practical exploration of social and usability issues by facilitating the prototyping and fine-tuning of context-aware applications.

Modelling and using imperfect context information

Most recently developed context-aware software applications make unrealistic assumptions about the quality of the available context information, which can lead to inappropriate actions by the application and frustration on the part of the user. Here, we explore the problem of imperfect context information and some of its causes, and propose a novel approach for modelling incomplete and inaccurate information. Additionally, we present a discussion of our experiences in developing a context-aware communication application, highlighting design issues that are pertinent when developing applications that rely on imperfect context information.

Middleware for distributed context-aware systems

Context-aware systems represent extremely complex and heterogeneous distributed systems, composed of sensors, actuators, application components, and a variety of context processing components that manage the flow of context information between the sensors/actuators and applications. The need for middleware to seamlessly bind these components together is well recognised. Numerous attempts to build middleware or infrastructure for context-aware systems have been made, but these have provided only partial solutions; for instance, most have not adequately addressed issues such as mobility, fault tolerance or privacy. One of the goals of this paper is to provide an analysis of the requirements of a middleware for context-aware systems, drawing from both traditional distributed system goals and our experiences with developing context-aware applications. The paper also provides a critical review of several middleware solutions, followed by a comprehensive discussion of our own PACE middleware. Finally, it provides a comparison of our solution with the previous work, highlighting both the advantages of our middleware and important topics for future research.

Vertical handover supporting pervasive computing in future wireless networks

A variety of current and future wired and wireless networking technologies can be transformed into a seamless communication environments through application of context-based vertical handovers. Such seamless communication environments are needed for future pervasive/ubiquitous systems. Pervasive systems are context aware and need to adapt to context changes, including network disconnections and changes in network Quality of Service (QoS). Vertical handover is one of many possible adaptation methods. It allows users to roam freely between heterogeneous networks while maintaining the continuity of their applications. This paper proposes a vertical handover mechanism suitable for multimedia applications in pervasive systems. The paper focuses on the handover decision making process which uses context information regarding user devices, user location, network environment and requested QoS.

Dynamic conflict detection in policy-based management systems

While advances in open distributed systems have undoubtedly provided a uniquely diverse environment for users, managing the resources within such an environment has become an increasingly complex task. This challenge has been considered for several years within the distributed systems management research community and we have recently seen policy-based management emerge as one such promising exemplification. The focus of our work has been predominantly on supporting the requirements of large evolving enterprises. Such environments present a significant challenge for policy-based management as the fluidity and complexity of interactions occurring in such environments mean that prevailing static-based specification and analysis of policies and roles, would be inadequate in many instances. We are therefore interested in providing support for a dynamic policy-based management environment. This paper discusses the critical nature of providing both dynamic and static conflict detection and resolution and introduces a scalable computationally-efficient dynamic conflict detection mechanism.

Methods for conflict resolution in policy-based management systems

While developments in distributed object computing environments, such as the Common Object Request Broker Architecture (CORBA) by the Object Management Group (2000) and the Telecommunication Intelligent Network Architecture (TINA) by H. Mulder (2002), have enabled interoperability between domains in large open distributed systems, managing the resources within such systems has become an increasingly complex task. This challenge has been considered for several years within the distributed systems management research community and policy-based management has recently emerged as a promising solution. Large evolving enterprises present a significant challenge for policy-based management partly due to the requirement to support both mutual transparency and individual autonomy between domains according to C. Bidan and V. Issarny (1998), but also because the fluidity and complexity of interactions occurring within such environments requires an ability to cope with the existence of multiple, potentially inconsistent policies. This paper discusses the need for providing both dynamic (run-time) and static (compile-time) conflict detection and resolution for policies in such systems and builds on our earlier conflict detection work (Dunlop et al., 2001, 2002) to introduce the methods for conflict resolution in large open distributed systems.

An Autonomic Context Management System for Pervasive Computing

Context-aware applications adapt to changing computing environments or changing user circumstances/tasks. Context information that supports such adaptations is provided by the underlying infrastructure, which gathers, pre-processes and provisions context information from a variety of context information sources. Such an infrastructure is prone to failures and disconnections that negatively impact on the ability of context-aware applications to adapt (and therefore dramatically impact on their usability). This paper describes a model-based autonomic context management system (ACoMS) that can dynamically configure and reconfigure its context information gathering and pre-processing functionality in order to provide fault tolerant provisioning of context information. The approach uses standards based descriptions of context information sources to increase openness, interoperability and scalability of context-aware systems.