Q-CAD: QoS and Context Aware Discovery framework for adaptive mobile systems

This paper presents Q-CALl, a resource discovery framework that enables pervasive computing applications to discover and select the resource(s) best satisfying the user needs, taking the current execution context and quality-ofservice (QoS} requirements into account. The available resources are first screened, so that only those suirable to the current execution context of the application will be considered; the shortlisted resources are then evaluated against the QoS needs of the application, and a binding is established to the best available

Context-Aware Framework for Performance Tuning via Multi-action Evaluation

Context-aware systems perform adaptive changes in several ways. One way is for the system developers to encompass all possible context changes in a context-aware application and embed them into the system. However, this may not suit situations where the system encounters unknown contexts. In such cases, system inferences and adaptive learning are used whereby the system executes one action and evaluates the outcome to self-adapts/self-learns based on that. Unfortunately, this iterative approach is time-consuming if high number of actions needs to be evaluated. By contrast, our framework for context-aware systems finds the best action for unknown context through concurrent multi-action evaluation and self-adaptation which reduces significantly the evolution time in comparison to the iterative approach. In our implementation we show how the context-aware multi-action system can be used for a context-aware evaluation for database performance tuning

Context-driven methodologies for context-aware and adaptive systems

Applications which are both context-aware and adapting, enhance users’ experience by anticipating their need in relation with their environment and adapt their behavior according to environmental changes. Being by definition both context-aware and adaptive these applications suffer both from faults related to their context-awareness and to their adaptive nature plus from a novel variety of faults originated by the combination of the two. This research work analyzes, classifies, detects, and reports faults belonging to this novel class aiming to improve the robustness of these Context-Aware Adaptive Applications (CAAAs). To better understand the peculiar dynamics driving the CAAAs adaptation mechanism a general high-level architectural model has been designed. This architectural model clearly depicts the stream of information coming from sensors and being computed all the way to the adaptation mechanism. The model identifies a stack of common components representing increasing abstractions of the context and their general interconnections. Known faults involving context data can be re-examined according to this architecture and can be classified in terms of the component in which they are happening and in terms of their abstraction from the environment. Resulting from this classification is a CAAA-oriented fault taxonomy. Our architectural model also underlines that there is a common evolutionary path for CAAAs and shows the importance of the adaptation logic. Indeed most of the adaptation failures are caused by invalid interpretations of the context by the adaptation logic. To prevent such faults we defined a model, the Adaptation Finite-State Machine (A-FSM), describing how the application adapts in response to changes in the context. The A-FSM model is a powerful instrument which allows developers to focus in those context-aware and adaptive aspects in which faults reside. In this model we have identified a set of patterns of faults representing the most common faults in this application domain. Such faults are represented as violation of given properties in the A-FSM. We have created four techniques to detect such faults. Our proposed algorithms are based on three different technologies: enumerative, symbolic and goal planning. Such techniques compensate each other. We have evaluated them by comparing them to each other using both crafted models and models extracted from existing commercial and free applications. In the evaluation we observe the validity, the readability of the reported faults, the scalability and their behavior in limited memory environments. We conclude this Thesis by suggesting possible extensions

Supporting policy-based contextual reconfiguration and adaptation in ubiquitous computing

In order for pervasive computing systems to be able to perform tasks which support us in everyday life without requiring attention from the users of the environment, they need to adapt themselves in response to context. This makes context-awareness in general, and context-aware adaptation in particular, an essential requirement for pervasive computing systems. Two of the features of context-awareness are: contextual reconfiguration and contextual adaptation in which applications adapt their behaviour in response to context. We combine both these features of context-awareness to provide a broad scope of adaptation and put forward a system, called Policy-Based Contextual Reconfiguration and Adaptation (PCRA) that provides runtime support for both. The combination of both context-aware reconfiguration and context-aware adaptation provides a broad scope of adaptation and hence allows the development of diverse adaptive context-aware applications. However, another important issue is the choice of an effective means for developing, modifying and extending such applications. The main argument forming the basis of this thesis is that we advocate the use of a policy-based programming model and argue that it provides more effective means for developing, modifying and extending such applications. This thesis addresses other important surrounding issues which are associated with adaptive context-aware applications. These include the management of invalid bindings and the provision of seamless caching support for remote services involved in bindings for improved performance. The bindings may become invalid due to failure conditions that can arise due to network problems or migration of software components, causing bindings between the application component and remote service to become invalid. We have integrated reconfiguration support to manage bindings, and seamless caching support for remote services in PCRA. This thesis also describes the design and implementation of PCRA, which enables development of adaptive context-aware applications using policy specifications. Within PCRA, adaptive context-aware applications are modelled by specifying binding policies and adaptation policies. The use of policies within PCRA simplifies the development task because policies are expressed at a high-level of abstraction, and are expressed independently of each other. PCRA also allows the dynamic modification of applications since policies are independent units of execution and can be dynamically loaded and removed from the system. This is a powerful and useful capability as applications may evolve over time, i.e. the user needs and preferences may change, but re-starting is undesirable. We evaluate PCRA by comparing its features to other systems in the literature, and by performance measures

Exploring the motivations involved in context aware services

This paper reports on research focused upon understanding the factors influencing the effective use of context aware adaptive systems. Unlike many desktop applications, ubiquitous computing supports users in dynamic situations by utilizing surrounding context to help them manage and utilise technology. It is by its nature highly dynamic since it responds to changes in context of use, and this brings new challenges to interaction design. In particular, there is still little research into human factors relating to the effectiveness and appropriateness of ubiquitous computing concepts. We review theoretical factors regarding human user’s motivation, emotion, perception and preference that are relevant to evaluating ubiquitous computing. Here we then report on empirical research relating these theoretical factors to the use of contextually aware adaptive systems. The results show that there is a significant difference in users' preferences between intrinsic and extrinsic motivations. The other findings identify the importance and role of user involvement in decision-making processes. Overall the work raises interesting questions about the nature of empirical research as a methodology of relevance to adaptive system design

Quality of Context in Context-Aware Systems

Context-aware Systems (CASs) are becoming increasingly popular and can be found in the areas of wearable computing, mobile computing, robotics, adaptive and intelligent user interfaces. Sensors are the corner stone of context capturing however, sensed context data are commonly prone to imperfection due to the technical limitations of sensors, their availability, dysfunction, and highly dynamic nature of environment. Consequently, sensed context data might be imprecise, erroneous, conflicting, or simply missing. To limit the impact of context imperfection on the behavior of a context-aware system, a notion of Quality of Context (QoC) is used to measure quality of any information that is used as context information. Adaptation is performed only if the context data used in the decision-making has an appropriate quality level. This paper reports an analytical review for state of the art quality of context in context-aware systems and points to future research directions

Collaborative Authoring of Adaptive Educational Hypermedia by Enriching a Semantic Wiki’s Output

This research is concerned with harnessing collaborative approaches for the authoring of Adaptive Educational Hypermedia (AEH) systems. It involves the enhancement of Semantic Wikis with pedagogy aware features to this end. There are many challenges in understanding how communities of interest can efficiently collaborate for learning content authoring, in introducing pedagogy to the developed knowledge models and in specifying user models for efficient delivery of AEH systems. The contribution of this work will be the development of a model of collaborative authoring which includes domain specification, content elicitation, and definition of pedagogic approach. The proposed model will be implemented in a prototype AEH authoring system that will be tested and evaluated in a formal education context

User-Centered Context-Aware Mobile Applications―The Next Generation of Personal Mobile Computing

Context-aware mobile applications are systems that can sense clues about the situational environment and enable appropriate mechanisms of interaction between end users and systems, making mobile devices more intelligent, adaptive, and personalized. In order to better understand such systems and the potentials and barriers of their development and practical use, this paper provides a state-of-the-art overview of this emerging field. Unlike previous literature reviews that mainly focus on technological aspects of such systems, we examine this field mainly from application and research methodology perspectives. We will present major types of current context-aware mobile applications, and discuss research methodologies used in existing studies and their limitations, and highlight potential future research