Managing contextual information in semantically-driven temporal information systems

Context-aware (CA) systems have demonstrated the provision of a robust solution for personalized information delivery in the current content-rich and dynamic information age we live in. They allow software agents to autonomously interact with users by modeling the user’s environment (e.g. profile, location, relevant public information etc.) as dynamically-evolving and interoperable contexts. There is a flurry of research activities in a wide spectrum at context-aware research areas such as managing the user’s profile, context acquisition from external environments, context storage, context representation and interpretation, context service delivery and matching of context attributes to users‘ queries etc. We propose SDCAS, a Semantic-Driven Context Aware System that facilitates public services recommendation to users at temporal location. This paper focuses on information management and service recommendation using semantic technologies, taking into account the challenges of relationship complexity in temporal and contextual information

Consumer Value of Context Aware and Location Based Mobile Services

Context aware services have the ability to utilize information about the user’s context to adapt services to the user’s current situation and needs. In this paper we consider users’ perceptions of the added value of location awareness and presence information in mobile services. We use an experimental design, where stimuli comprising specific bundles of mobile services were presented to groups of respondents. The stimuli showed increasing, manipulated, levels of contextawareness, including location of the user and location and availability of buddies as distinct levels. Our results indicate that simply adding context aware features to mobile services does not necessarily provide added value to users, rather the contrary. The potential added value of insight in buddies’ location and availability is offset by people’s reluctance to share location information with others. Although the average perceived value overall is rather low there exists a substantial minority that does appreciate the added context aware features. High scores on constructs like product involvement, social influence and self-expressiveness characterize this group. The results also show that context aware service bundles with utilitarian elements have a higher perceived value than bundles with hedonic elements. On the basis of the different results some guidelines for designing context aware mobile services are formulated

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work

IoT data processing pipeline in FoF perspective

With the development in the contemporary industry, the concepts of ICT and IoT are gaining more importance, as they are the foundation for the systems of the future. Most of the current solutions converge into transforming the traditional industry in new smart interconnected factories, aware of its context, adaptable to different environments and capable of fully using its resources. However, the full potential for ICT manufacturing has not been achieved, since there is not a universal or standard architecture or model that can be applied to all the existing systems, to tackle the heterogeneity of the existing devices. In a common factory, exists a large amount of information that needs to be processed into the system in order to define event rules accordingly to the related contextual knowledge, to later execute the needed actions. However, this information is sometimes heterogeneous, meaning that it cannot be accessed or understood by the components of the system. This dissertation analyses the existing theories and models that may lead to seamless and homogeneous data exchange and contextual interpretation. A framework based on these theories is proposed in this dissertation, that aims to explore the situational context formalization in order to adequately provide appropriate actions

Feature-based generation of pervasive systems architectures utilizing software product line concepts

As the need for pervasive systems tends to increase and to dominate the computing discipline, software engineering approaches must evolve at a similar pace to facilitate the construction of such systems in an efficient manner. In this thesis, we provide a vision of a framework that will help in the construction of software product lines for pervasive systems by devising an approach to automatically generate architectures for this domain. Using this framework, designers of pervasive systems will be able to select a set of desired system features, and the framework will automatically generate architectures that support the presence of these features. Our approach will not compromise the quality of the architecture especially as we have verified that by comparing the generated architectures to those manually designed by human architects. As an initial step, and in order to determine the most commonly required features that comprise the widely most known pervasive systems, we surveyed more than fifty existing architectures for pervasive systems in various domains. We captured the most essential features along with the commonalities and variabilities between them. The features were categorized according to the domain and the environment that they target. Those categories are: General pervasive systems, domain-specific, privacy, bridging, fault-tolerance and context-awareness. We coupled the identified features with well-designed components, and connected the components based on the initial features selected by a system designer to generate an architecture. We evaluated our generated architectures against architectures designed by human architects. When metrics such as coupling, cohesion, complexity, reusability, adaptability, modularity, modifiability, packing density, and average interaction density were used to test our framework, our generated architectures were found comparable, if not better than the human generated architectures

Context in Mobile System Design: Characterization, Theory, and Implications

Context information brings new opportunities for efficient and effective applications and services on mobile devices. Many existing work exploit the context dependency of mobile usage for specific applications, and show significant, quantified, performance gains by utilizing context. In order to be practical, such works often pay careful attention to the energy and processing costs of context awareness while attempting to maintain reasonable accuracy. These works also have to deal with the challenges of multiple sources of context, which can lead to a sparse training data set. Even with the abundance of such work, quantifying context-dependency and the relationship between context-dependency and performance achievements remains an open problem, and solutions to manage the and challenges of context awareness remain ad-hoc. To this end, this dissertation methodologically quantifies and measures the context dependency of three principal types of mobile usage in a methodological, application agnostic yet practical manner. The three usages are the websites the user visits, the phone numbers they call, and the apps they use, either built-in or obtained by the user from the App Store . While this dissertation measures the context dependency of these three principal types of mobile usage, its methodology can be readily extended to other context-dependent mobile usage and system resources. This dissertation further presents SmartContext, a framework to systematically optimize the energy cost of context awareness by selecting among different context sources, while satisfying the system designer’s cost-accuracy tradeoffs. Finally, this thesis investigates the collective effect of social context on mobile usage, by separating and comparing LiveLab users based on their socioeconomic groups. The analysis and findings are based on usage and context traces collected in real-life settings from 24 iPhone users over a period of one year. This dissertation presents findings regarding the context dependency of three principal types of mobile usage; visited websites, phone calls, and app usage. The methodology and lessons presented here can be readily extended to other forms of context and context-dependent usage and resources. They guide the development of context aware systems, and highlight the challenges and expectations regarding the context dependency of mobile usage

Courtier en qualité de contexte pour les applications mobiles

Résumé Plusieurs travaux de recherche ont mis en évidence la nécessité de la prise en charge de la qualité des informations de contexte pour les applications mobiles sensibles aux contextes. Différentes architectures permettant la gestion de la qualité du contexte (QdC) ont étudié proposées. Bien que ces solutions identifient les métriques de QdC les plus pertinentes, proposent des méthodes de quantification pour ces métriques, ou encore expliquent comment exploiter les données sur la QdC, peu abordent l'interface entre les sources d'information de contexte et leurs destinataires. En eet, lorsque deux sources sont disponibles pour la mème information de contexte, il est utile de disposer d'un mécanisme permettant de déterminer la source offrant la QdC adéquate. Dans ce mémoire, nous proposons une modélisation de la qualité de contexte ainsi que la spécification et l'implémentation d'une architecture offrant un mécanisme de sélection d'un fournisseur de contexte garantissant le respect des besoins en qualité de contexte des consommateurs. Nos principaux objectifs sont la minimisation de la charge des fournisseurs et consommateurs et la minimisation de la signalisation. Notre solution se caractérise par la mise en place d'un système de courtage entre les fournisseurs d'information de contexte et leurs consommateurs. Le courtier, entité centrale, prend en charge la gestion de la qualité de contexte. Le consommateur se réfère au courtier afin de se voir attribuer un fournisseur répondant à ses besoins. Il peut alors envoyer ses requêtes de contexte. Notre modèle de qualité de contexte suppose une formulation simple de celle-ci par les consommateurs et fournisseurs. Au final, la spécification de notre architecture suppose le respect de nos deux premiers objectifs. De plus, les tests menés sur notre implémentation du courtier en qualité de contexte confirme que nous les avons atteint. An de mesurer notre contribution à la recherche nous avons comparé nos travaux à ceux d'autres chercheurs et constaté une amélioration des possibilitées de mise à l'échelle offert par notre architecture.----------Abstract Research has already highlighted the need to support quality of context information in context-aware mobile applications. Various architectures enabling the management of quality of context (QoC) has been proposed. Although these solutions identify the most relevant metrics of QoC, oer methods of quantication for these metrics, or explain how to use data on QoC, only a few consider the interface between the sources of context and their recipients. Actually, when two sources are available for the same context information, it becomes useful to have a mechanism to determine the source oering suitable QoC. In this thesis, we propose a model of quality of context, the specication and implementation of an architecture providing a mechanism for selecting a context provider which ensure that the quality of context oered by the provider complies the consumer needs. Our main objectives are the minimization of the providers and consumers workload, and the minimization of the overhead. Our solution is to set up a brokerage system between context information providers and their consumers. The broker, central element, supports the management of the quality of context. The consumer refers to the broker to be assigned a provider that meets its needs. It can then send context queries. Our model of quality of context oer a simple formulation, which is benecial to the reduction of consumers and suppliers workload. Finally, the specication of our architecture predicate the respect of our rst two objectives. Moreover, experiments conducted on our implementation of the quality of context broker conrms that we have achieved our objectives. To measure our contribution to the research we have compared our work with other research and found that our architecture oer better opportunities for scaling