12 resultados para user context

em University of Queensland eSpace - Australia


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Applications that exploit contextual information in order to adapt their behaviour to dynamically changing operating environments and user requirements are increasingly being explored as part of the vision of pervasive or ubiquitous computing. Despite recent advances in infrastructure to support these applications through the acquisition, interpretation and dissemination of context data from sensors, they remain prohibitively difficult to develop and have made little penetration beyond the laboratory. This situation persists largely due to a lack of appropriately high-level abstractions for describing, reasoning about and exploiting context information as a basis for adaptation. In this paper, we present our efforts to address this challenge, focusing on our novel approach involving the use of preference information as a basis for making flexible adaptation decisions. We also discuss our experiences in applying our conceptual and software frameworks for context and preference modelling to a case study involving the development of an adaptive communication application.

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Vertical handovers can transform heterogeneous networks into an integrated communication environment. Such integration can lead to seamless communication if context information is used to support vertical handovers. Seamless communication environments are needed for future pervasive/ubiquitous systems, which are context aware and can adapt to context changes, including network disconnections, changes in network quality of service and changes in user preferences. This paper describes a generic, context-aware handover solution for multimedia applications and illustrates how this handover works for redirection of communication between WLANs and GPRS or UMTS networks. A description of a prototype for WLAN/GPRS handover and the results of handover experiments are also presented.

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Most recently developed context-aware software applicationsmake 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. In this paper, 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 contextaware communication application, highlighting design issues that are pertinent when developing applications that rely on imperfect context information.

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Context information is used by pervasive networking and context-aware programs to adapt intelligently to different environments and user tasks. As the context information is potentially sensitive, it is often necessary to provide privacy protection mechanisms for users. These mechanisms are intended to prevent breaches of user privacy through unauthorised context disclosure. To be effective, such mechanisms should not only support user specified context disclosure rules, but also the disclosure of context at different granularities. In this paper we describe a new obfuscation mechanism that can adjust the granularity of different types of context information to meet disclosure requirements stated by the owner of the context information. These requirements are specified using a preference model we developed previously and have since extended to provide granularity control. The obfuscation process is supported by our novel use of ontological descriptions that capture the granularity relationship between instances of an object type.

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Pervasive computing applications must be engineered to provide unprecedented levels of flexibility in order to reconfigure and adapt in response to changes in computing resources and user requirements. To meet these challenges, appropriate software engineering abstractions and infrastructure are required as a platform on which to build adaptive applications. In this paper, we demonstrate the use of a disciplined, model-based approach to engineer a context-aware Session Initiation Protocol (SIP) based communication application. This disciplined approach builds on our previously developed conceptual models and infrastructural components, which enable the description, acquisition, management and exploitation of arbitrary types of context and user preference information to enable adaptation to context changes

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Context-aware applications rely on implicit forms of input, such as sensor-derived data, in order to reduce the need for explicit input from users. They are especially relevant for mobile and pervasive computing environments, in which user attention is at a premium. To support the development of context-aware applications, techniques for modelling context information are required. These must address a unique combination of requirements, including the ability to model information supplied by both sensors and people, to represent imperfect information, and to capture context histories. As the field of context-aware computing is relatively new, mature solutions for context modelling do not exist, and researchers rely on information modelling solutions developed for other purposes. In our research, we have been using a variant of Object-Role Modeling (ORM) to model context. In this paper, we reflect on our experiences and outline some research challenges in this area.

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Pervasive computing applications must be sufficiently autonomous to adapt their behaviour to changes in computing resources and user requirements. This capability is known as context-awareness. In some cases, context-aware applications must be implemented as autonomic systems which are capable of dynamically discovering and replacing context sources (sensors) at run-time. Unlike other types of application autonomy, this kind of dynamic reconfiguration has not been sufficiently investigated yet by the research community. However, application-level context models are becoming common, in order to ease programming of context-aware applications and support evolution by decoupling applications from context sources. We can leverage these context models to develop general (i.e., application-independent) solutions for dynamic, run-time discovery of context sources (i.e., context management). This paper presents a model and architecture for a reconfigurable context management system that supports interoperability by building on emerging standards for sensor description and classification.

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A major requirement for pervasive systems is to integrate context-awareness to support heterogeneous networks and device technologies and at the same time support application adaptations to suit user activities. However, current infrastructures for pervasive systems are based on centralized architectures which are focused on context support for service adaptations in response to changes in the computing environment or user mobility. In this paper, we propose a hierarchical architecture based on active nodes, which maximizes the computational capabilities of various nodes within the pervasive computing environment, while efficiently gathering and evaluating context information from the user's working environment. The migratable active node architecture employs various decision making processes for evaluating a rich set of context information in order to dynamically allocate active nodes in the working environment, perform application adaptations and predict user mobility. The active node also utilizes the Redundant Positioning System to accurately manage user's mobility. This paper demonstrates the active node capabilities through context-aware vertical handover applications.