yes / The complexity of pervasive systems arises from the many different aspects that such systems possess. A typical pervasive system may be autonomous, distributed, concurrent and context-based, and may involve humans and robotic devices working together. If we wish to formally verify the behaviour of such systems, the formal methods for pervasive systems will surely also be complex. In this paper, we move towards being able to formally verify pervasive systems and outline our approach wherein we distinguish four distinct dimensions within pervasive system behaviour and utilise different, but appropriate, formal techniques for verifying each one. / EPSRC

Context-awareness in pervasive computing environments can reduce user interactions with computing devices by making applications adaptive and autonomous. Context-aware applications rely on information about user context and user preferences to guide their own behaviour. However, context-aware applications do not always behave as users expect due to imperfection of context information, incorrect user preferences or incorrect adaptation rules. This may cause users to feel loss of control over their applications. To mitigate these problems, context-aware systems must provide mechanisms to strike a suitable balance between user control and software autonomy. Allowing users to scrutinise the system and allowing the system to sometimes include users in the adaptation decision making, can provide a balance of user control. This thesis addresses the shortcoming in development of context-aware pervasive systems with regard to providing balance between user control and software autonomy. The thesis shows that rather than making a context-aware application a complete black box, it is possible to allow user control of application adaptations. The system can reveal to the user what context information the system uses and how it arrives at adaptation decisions if the user requests such information. The user may decide to alter the adaptive behaviour of the system to achieve desired outcomes. Hence, a context-aware application becomes a closed loop system where the user is put into the loop if requested. The proposed approach is developed under an assumption that users differ in the level of their technology expertise and therefore the system has to provide explanations that are suitable for a particular level of user expertise. The thesis makes two important research contributions: design of the architectural framework and development of the platform exposing autonomic behaviour of context-aware applications. The architectural framework supports developers of context aware-applications in providing balance of control between users and software autonomy. The framework describes a set of models that allow revealing the adaptation behaviour of context-aware applications in a way suitable for users with various levels of expertise. The framework consists of: (i) a model for exposing elements that influence the context-aware behaviour, (ii) a generic architecture for providing balance of control, (iii) a user model, and (iv) a context graph based overview of context-aware adaptations. The platform exposing autonomic behaviour of context-aware applications is a proof of concept prototype of a software infrastructure (middleware) providing balance of control. The software infrastructure includes: (i) a Semantic Manager, developed to serve the description of elements required for explanations of the application behaviour; (ii) an extension of the PACE Middleware, to enable the middleware to expose the context information, preferences, adaptation rules and their evaluation traces, respectively. (iii) supporting tools for the application designer to prepare the overview of context-aware adaptations and review the evaluation traces. Finally, this thesis presents a case study that illustrates and evaluates the system supporting balance of control. This evaluation involves the existing application which is developed using the previous version of the PACE middleware. The case study validates the architectural framework and illustrates the process and issues involved in developing context-aware application that are able to expose elements that influence context-aware behaviour.

Au cours des dernières années, il y a un intérêt croissant pour les systèmes logiciels capables de faire face à la dynamique des environnements en constante évolution. Actuellement, les systèmes auto-adaptatifs sont nécessaires pour l’adaptation dynamique à des situations nouvelles en maximisant performances et disponibilité. Les systèmes ubiquitaires et pervasifs fonctionnent dans des environnements complexes et hétérogènes et utilisent des dispositifs à ressources limitées où des événements peuvent compromettre la qualité du système. En conséquence, il est souhaitable de s’appuyer sur des mécanismes d’adaptation du système en fonction des événements se produisant dans le contexte d’exécution. En particulier, la communauté du génie logiciel pour les systèmes auto-adaptatif (Software Engineering for Self-Adaptive Systems - SEAMS) s’efforce d’atteindre un ensemble de propriétés d’autogestion dans les systèmes informatiques. Ces propriétés d’autogestion comprennent les propriétés dites self-configuring, self-healing, self-optimizing et self-protecting. Afin de parvenir à l’autogestion, le système logiciel met en œuvre un mécanisme de boucle de commande autonome nommé boucle MAPE-K [78]. La boucle MAPE-K est le paradigme de référence pour concevoir un logiciel auto-adaptatif dans le contexte de l’informatique autonome. Cet modèle se compose de capteurs et d’effecteurs ainsi que quatre activités clés : Monitor, Analyze, Plan et Execute, complétées d’une base de connaissance appelée Knowledge, qui permet le passage des informations entre les autres activités [78]. L’étude de la littérature récente sur le sujet [109, 71] montre que l’adaptation dynamique est généralement effectuée de manière réactive, et que dans ce cas les systèmes logiciels ne sont pas en mesure d’anticiper des situations problématiques récurrentes. Dans certaines situations, cela pourrait conduire à des surcoûts inutiles ou des indisponibilités temporaires de ressources du système. En revanche, une approche proactive n’est pas simplement agir en réponse à des événements de l’environnement, mais a un comportement déterminé par un but en prenant par anticipation des initiatives pour améliorer la performance du système ou la qualité de service. / In this thesis we proposed a proactive self-adaptation by integrating predictive analysis into two phases of the software process. At design time, we propose a predictive modeling process, which includes the activities: define goals, collect data, select model structure, prepare data, build candidate predictive models, training, testing and cross-validation of the candidate models and selection of the ''best'' models based on a measure of model goodness. At runtime, we consume the predictions from the selected predictive models using the running system actual data. Depending on the input data and the time allowed for learning algorithms, we argue that the software system can foresee future possible input variables of the system and adapt proactively in order to accomplish middle and long term goals and requirements.

To provide users with personalized adaptive services only using the accessible computing resources in a cloud environment, context aware applications need to assimilate both the accessed and derived context, i.e. a combination of more than one sensed data and information in the environment. Context data dependency, dependency that arises between the context data producer and consumer, may get introduced in a system due to numerous reasons. But as the number of context dependencies for a service increases, the more complex the system becomes to manage. The thesis addresses issues of how to identify context dependencies, represent such context dependencies and then reduce them in a system. In the first part of the thesis, we present two efficient approaches to determine context dependency relations among various services in ubiquitous computing environment to help better analyse the pervasive services. One approach is based on graph theory, and we have used the topological sort to determine the context dependencies. The second approach is based on solving constraint networks which determines whether an entity is affected when the state of a certain other entity has its state changed, i.e. determining the dynamic nature of context dependency. In the second part of the thesis, we present a mode for representation of context dependencies within a system. Our model that represents context dependencies is based on set theory and first-order predicate logic. The context dependency representation model also represents alternative sources for context acquisition that can be utilized in a case in which the preferred context producers are not available to service the desired context to the relevant context consumer any more. Further, we try to reduce the context dependencies by presenting the idea of profile context, which is based on the proposal of an open framework for context acquisition, management and distribution. This heuristic approach is based on the idea of utilizing mobile nodes in an ad hoc overlay network with more resources than the context producer itself to store various contextual information under the banner of profile context, and further, provide profile context instead of each context individually based on the queries the nodes receive from the context consumers. Bringing together the context information and context updates from various sources, support for context aware decisions can be implemented efficiently in a mobile environment by addressing the issues of context dependency using profile context

Pour fournir aux utilisateurs des services personnalisés d'adaptation en utilisant uniquement les ressources informatiques accessibles dans un environnement de cloud computing, les applications contexte, conscients besoin d'assimiler à la fois le contexte accessible et dérivés, c'est à dire une combinaison de plus d'un senti données et d'informations dans l'environnement. Contexte des données de dépendance, la dépendance qui se pose entre le contexte des données du producteur et du consommateur, peut se présenter dans un système en raison de nombreuses raisons. Mais comme le nombre de dépendances de contexte pour une augmentation des services, la plus complexe, le système devient à gérer. La thèse aborde les questions de la façon d'identifier les dépendances de contexte, représentent des dépendances de contexte tels, puis les réduire dans un système. Dans la première partie de la thèse, nous présentons deux approches efficaces pour déterminer les relations de dépendance entre les différents services du contexte dans l'environnement informatique ubiquitaire pour aider à mieux analyser les services omniprésents. Une approche est basée sur la théorie des graphes, et nous avons utilisé le tri topologique pour déterminer les dépendances de contexte. La deuxième approche est basée sur la résolution des réseaux de contraintes qui détermine si une entité est affectée lorsque l'état d'une certaine entité autre a changé son état, c.-à-détermination de la nature dynamique de la dépendance contexte. Dans la deuxième partie de la thèse, nous présentons un mode de représentation des dépendances de contexte au sein d'un système. Notre modèle qui représente les dépendances de contexte est basé sur la théorie des ensembles et la logique des prédicats du premier ordre. Le modèle de représentation contexte de dépendance représente également d'autres sources pour l'acquisition de contexte qui peuvent être utilisés dans une affaire dans laquelle les producteurs contexte privilégiées ne sont pas disponibles pour desservir le contexte souhaité pour le consommateur un contexte pertinent, pas plus. En outre, nous essayons de réduire les dépendances de contexte en présentant l'idée du contexte de profil, qui est basé sur la proposition d'un cadre ouvert pour l'acquisition de contexte, la gestion et la distribution. Cette approche heuristique est basée sur l'idée d'utiliser les nœuds mobiles dans un réseau ad hoc avec superposition de plus de ressources que le producteur lui-même contexte pour stocker diverses informations contextuelles sous la bannière du contexte profil, et en outre, fournir le contexte profil au lieu de chaque contexte individuellement sur la base sur les requêtes des nœuds reçoivent des consommateurs contexte. Réunissant les informations de contexte et de mises à jour de contexte à partir de diverses sources, le soutien aux décisions contexte, conscients peut être mis en œuvre efficacement dans un environnement mobile en s'attaquant aux problèmes de dépendance en utilisant le contexte contexte profil / To provide users with personalized adaptive services only using the accessible computing resources in a cloud environment, context aware applications need to assimilate both the accessed and derived context, i.e. a combination of more than one sensed data and information in the environment. Context data dependency, dependency that arises between the context data producer and consumer, may get introduced in a system due to numerous reasons. But as the number of context dependencies for a service increases, the more complex the system becomes to manage. The thesis addresses issues of how to identify context dependencies, represent such context dependencies and then reduce them in a system. In the first part of the thesis, we present two efficient approaches to determine context dependency relations among various services in ubiquitous computing environment to help better analyse the pervasive services. One approach is based on graph theory, and we have used the topological sort to determine the context dependencies. The second approach is based on solving constraint networks which determines whether an entity is affected when the state of a certain other entity has its state changed, i.e. determining the dynamic nature of context dependency. In the second part of the thesis, we present a mode for representation of context dependencies within a system. Our model that represents context dependencies is based on set theory and first-order predicate logic. The context dependency representation model also represents alternative sources for context acquisition that can be utilized in a case in which the preferred context producers are not available to service the desired context to the relevant context consumer any more. Further, we try to reduce the context dependencies by presenting the idea of profile context, which is based on the proposal of an open framework for context acquisition, management and distribution. This heuristic approach is based on the idea of utilizing mobile nodes in an ad hoc overlay network with more resources than the context producer itself to store various contextual information under the banner of profile context, and further, provide profile context instead of each context individually based on the queries the nodes receive from the context consumers. Bringing together the context information and context updates from various sources, support for context aware decisions can be implemented efficiently in a mobile environment by addressing the issues of context dependency using profile context

Made available in DSpace on 2015-05-14T12:36:38Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 4150986 bytes, checksum: 67f3a9455b63f5424ab2c9a531cf5090 (MD5) Previous issue date: 2012-05-24 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Several Governments and countries have shown great interest in defining public policies to reduce spending on health services. In this way, several researchers have sought to develop solutions that reduce such costs. Among these solutions are the remote monitoring systems of the State of health of critical patients, those suffering from heart disease, chronic diseases or elderly who need continuous care. These systems allow the identification of risk situations and the adoption of preventive procedures, reducing health spending. In addition, they allow an improvement in quality and lifetime of your users. Several approaches to the construction of these systems. Generally, they are divided into two main groups: the home care and the furniture. The approach used in this paper advocates the use of mobile monitoring systems can be more efficient, since the health monitoring will be carried out regardless of locale or patient drive. The work presented here makes use of pervasive devices for monitoring of the health status of patients with cardiovascular diseases, which are the biggest cause of death in the world. In this sense, this dissertation contributes with an application for use in mobile phones that act as an intelligent agent to the preventive monitoring of cardiovascular diseases, using a rules-based intelligence engine. This application, which has received the name of MonitorPrevIntel, based on the continuous reading of five physiological signals, detect abnormal situations of danger for the health of your server, and emits alarm procedures. To detect anomalous situations the application uses a mechanism fully embedded intelligence on the mobile phone, with custom knowledge base for each user. The alarms emitted by the system warn the user about the detection of abnormal situations and advise, via SMS messages, or trigger, via phone call, a medical center about this situation. The MonitorPrevIntel operation is controlled by your intelligence mechanism, based on the State of health of the user, allowing the same run autonomously, independently of the user activation. / Vários governos e países têm demonstrado bastante interesse em definir políticas públicas para reduzir os gastos com os serviços de saúde. Dessa maneira, diversos pesquisadores têm procurado desenvolver soluções que reduzam tais custos. Entre essas soluções, estão os sistemas de monitoramento remoto do estado de saúde de pacientes críticos, aqueles que sofrem de doenças cardíacas, doenças crônicas ou idosos que precisam de atendimento contínuo. Esses sistemas permitem a identificação de situações de risco e a adoção de procedimentos preventivos, o que reduz os gastos com saúde. Além disso, eles permitem uma melhoria na qualidade e no tempo de vida de seus usuários. Várias são as abordagens para construção desses sistemas. De maneira geral, elas se dividem em dois grandes grupos: os home care e os móveis. A abordagem utilizada nesse trabalho defende a utilização de sistemas de monitoramento móveis pode ser mais eficiente, uma vez que o acompanhamento da saúde será realizado independentemente da localidade ou da movimentação do paciente. O trabalho aqui apresentado faz uso de dispositivos pervasivos para monitoramento do estado de saúde de pacientes com doenças cardiovasculares, que são a maior causa de morte no mundo. Nesse sentido, esta dissertação contribui com um aplicativo para uso em telefones móveis que atue como um agente inteligente personalizado para o monitoramento preventivo de doenças cardiovasculares, utilizando um mecanismo de inteligência baseado em regras de produção. Esse aplicativo, que recebeu o nome de MonitorPrevIntel, com base na leitura contínua de cinco sinais fisiológicos, detecta situações anormais, de perigo para a saúde de seu usuário, e emite procedimentos de alarme. Para detectar as situações anômalas o aplicativo utiliza um mecanismo de inteligência totalmente embutido no telefone celular, com base de conhecimento personalizada para cada usuário. Os alarmes emitidos pelo sistema avisam ao usuário sobre a detecção de situações anormais de saúde e avisam, através de mensagens SMS, ou acionam, através de chamada telefônica, uma central médica sobre essa situação. O funcionamento do MonitorPrevIntel é controlado por seu mecanismo de inteligência, com base no estado de saúde do usuário, permitindo que o mesmo execute de maneira autônoma, independentemente da ativação pelo usuário.