148 research outputs found

    Context aware Sensor Networks

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    Pervasive computing reference architecture from a software engineering perspective (PervCompRA-SE)

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    Pervasive computing (PervComp) is one of the most challenging research topics nowadays. Its complexity exceeds the outdated main frame and client-server computation models. Its systems are highly volatile, mobile, and resource-limited ones that stream a lot of data from different sensors. In spite of these challenges, it entails, by default, a lengthy list of desired quality features like context sensitivity, adaptable behavior, concurrency, service omnipresence, and invisibility. Fortunately, the device manufacturers improved the enabling technology, such as sensors, network bandwidth, and batteries to pave the road for pervasive systems with high capabilities. On the other hand, this domain area has gained an enormous amount of attention from researchers ever since it was first introduced in the early 90s of the last century. Yet, they are still classified as visionary systems that are expected to be woven into people’s daily lives. At present, PervComp systems still have no unified architecture, have limited scope of context-sensitivity and adaptability, and many essential quality features are insufficiently addressed in PervComp architectures. The reference architecture (RA) that we called (PervCompRA-SE) in this research, provides solutions for these problems by providing a comprehensive and innovative pair of business and technical architectural reference models. Both models were based on deep analytical activities and were evaluated using different qualitative and quantitative methods. In this thesis we surveyed a wide range of research projects in PervComp in various subdomain areas to specify our methodological approach and identify the quality features in the PervComp domain that are most commonly found in these areas. It presented a novice approach that utilizes theories from sociology, psychology, and process engineering. The thesis analyzed the business and architectural problems in two separate chapters covering the business reference architecture (BRA) and the technical reference architecture (TRA). The solutions for these problems were introduced also in the BRA and TRA chapters. We devised an associated comprehensive ontology with semantic meanings and measurement scales. Both the BRA and TRA were validated throughout the course of research work and evaluated as whole using traceability, benchmark, survey, and simulation methods. The thesis introduces a new reference architecture in the PervComp domain which was developed using a novel requirements engineering method. It also introduces a novel statistical method for tradeoff analysis and conflict resolution between the requirements. The adaptation of the activity theory, human perception theory and process re-engineering methods to develop the BRA and the TRA proved to be very successful. Our approach to reuse the ontological dictionary to monitor the system performance was also innovative. Finally, the thesis evaluation methods represent a role model for researchers on how to use both qualitative and quantitative methods to evaluate a reference architecture. Our results show that the requirements engineering process along with the trade-off analysis were very important to deliver the PervCompRA-SE. We discovered that the invisibility feature, which was one of the envisioned quality features for the PervComp, is demolished and that the qualitative evaluation methods were just as important as the quantitative evaluation methods in order to recognize the overall quality of the RA by machines as well as by human beings

    Abstracting Application Development for Resource Constrained Wireless Sensor Networks

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    Ubiquitous computing is a concept whereby computing is distributed across smart objects surrounding users, creating ambient intelligence. Ubiquitous applications use technologies such as the Internet, sensors, actuators, embedded computers, wireless communication, and new user interfaces. The Internet-of-Things (IoT) is one of the key concepts in the realization of ubiquitous computing, whereby smart objects communicate with each other and the Internet. Further, Wireless Sensor Networks (WSNs) are a sub-group of IoT technologies that consist of geographically distributed devices or nodes, capable of sensing and actuating the environment.WSNs typically contain tens to thousands of nodes that organize and operate autonomously to perform application-dependent sensing and sensor data processing tasks. The projected applications require nodes to be small in physical size and low-cost, and have a long lifetime with limited energy resources, while performing complex computing and communications tasks. As a result, WSNs are complex distributed systems that are constrained by communications, computing and energy resources. WSN functionality is dynamic according to the environment and application requirements. Dynamic multitasking, task distribution, task injection, and software updates are required in field experiments for possibly thousands of nodes functioning in harsh environments.The development of WSN application software requires the abstraction of computing, communication, data access, and heterogeneous sensor data sources to reduce the complexities. Abstractions enable the faster development of new applications with a better reuse of existing software, as applications are composed of high-level tasks that use the services provided by the devices to execute the application logic.The main research question of this thesis is: What abstractions are needed for application development for resource constrained WSNs? This thesis models WSN abstractions with three levels that build on top of each other: 1) node abstraction, 2) network abstraction, and 3) infrastructure abstraction. The node abstraction hides the details in the use of the sensing, communication, and processing hardware. The network abstraction specifies methods of discovering and accessing services, and distributing processing in the network. The infrastructure abstraction unifies different sensing technologies and infrastructure computing platforms.As a contribution, this thesis presents the abstraction model with a review of each abstraction level. Several designs for each of the levels are tested and verified with proofs of concept and analyses of field experiments. The resulting designs consist of an operating system kernel, a software update method, a data unification interface, and all abstraction levels combining abstraction called an embedded cloud.The presented operating system kernel has a scalable overhead and provides a programming approach similar to a desktop computer operating system with threads and processes. An over-the-air update method combines low overhead and robust software updating with application task dissemination. The data unification interface homogenizes the access to the data of heterogeneous sensor networks. A unification model is used for various use cases by mapping everything as measurements. The embedded cloud allows resource constrained WSNs to share services and data, and expand resources with other technologies. The embedded cloud allows the distributed processing of applications according to the available services. The applications are implemented as processes using a hardware independent description language that can be executed on resource constrained WSNs. The lessons of practical field experimenting are analyzed to study the importance of the abstractions. Software complexities encountered in the field experiments highlight the need for suitable abstractions.The results of this thesis are tested using proof of concept implementations on real WSN hardware which is constrained by computing power in the order of a few MIPS, memory sizes of a few kilobytes, and small sized batteries. The results will remain usable in the future, as the vast amount, tight integration, and low-cost of future IoT devices require the combination of complex computation with resource constrained platforms

    Ami-deu : un cadre sémantique pour des applications adaptables dans des environnements intelligents

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    Cette thèse vise à étendre l’utilisation de l'Internet des objets (IdO) en facilitant le développement d’applications par des personnes non experts en développement logiciel. La thèse propose une nouvelle approche pour augmenter la sémantique des applications d’IdO et l’implication des experts du domaine dans le développement d’applications sensibles au contexte. Notre approche permet de gérer le contexte changeant de l’environnement et de générer des applications qui s’exécutent dans plusieurs environnements intelligents pour fournir des actions requises dans divers contextes. Notre approche est mise en œuvre dans un cadriciel (AmI-DEU) qui inclut les composants pour le développement d’applications IdO. AmI-DEU intègre les services d’environnement, favorise l’interaction de l’utilisateur et fournit les moyens de représenter le domaine d’application, le profil de l’utilisateur et les intentions de l’utilisateur. Le cadriciel permet la définition d’applications IoT avec une intention d’activité autodécrite qui contient les connaissances requises pour réaliser l’activité. Ensuite, le cadriciel génère Intention as a Context (IaaC), qui comprend une intention d’activité autodécrite avec des connaissances colligées à évaluer pour une meilleure adaptation dans des environnements intelligents. La sémantique de l’AmI-DEU est basée sur celle du ContextAA (Context-Aware Agents) – une plateforme pour fournir une connaissance du contexte dans plusieurs environnements. Le cadriciel effectue une compilation des connaissances par des règles et l'appariement sémantique pour produire des applications IdO autonomes capables de s’exécuter en ContextAA. AmI- DEU inclut également un outil de développement visuel pour le développement et le déploiement rapide d'applications sur ContextAA. L'interface graphique d’AmI-DEU adopte la métaphore du flux avec des aides visuelles pour simplifier le développement d'applications en permettant des définitions de règles étape par étape. Dans le cadre de l’expérimentation, AmI-DEU comprend un banc d’essai pour le développement d’applications IdO. Les résultats expérimentaux montrent une optimisation sémantique potentielle des ressources pour les applications IoT dynamiques dans les maisons intelligentes et les villes intelligentes. Notre approche favorise l'adoption de la technologie pour améliorer le bienêtre et la qualité de vie des personnes. Cette thèse se termine par des orientations de recherche que le cadriciel AmI-DEU dévoile pour réaliser des environnements intelligents omniprésents fournissant des adaptations appropriées pour soutenir les intentions des personnes.Abstract: This thesis aims at expanding the use of the Internet of Things (IoT) by facilitating the development of applications by people who are not experts in software development. The thesis proposes a new approach to augment IoT applications’ semantics and domain expert involvement in context-aware application development. Our approach enables us to manage the changing environment context and generate applications that run in multiple smart environments to provide required actions in diverse settings. Our approach is implemented in a framework (AmI-DEU) that includes the components for IoT application development. AmI- DEU integrates environment services, promotes end-user interaction, and provides the means to represent the application domain, end-user profile, and end-user intentions. The framework enables the definition of IoT applications with a self-described activity intention that contains the required knowledge to achieve the activity. Then, the framework generates Intention as a Context (IaaC), which includes a self-described activity intention with compiled knowledge to be assessed for augmented adaptations in smart environments. AmI-DEU framework semantics adopts ContextAA (Context-Aware Agents) – a platform to provide context-awareness in multiple environments. The framework performs a knowledge compilation by rules and semantic matching to produce autonomic IoT applications to run in ContextAA. AmI-DEU also includes a visual tool for quick application development and deployment to ContextAA. The AmI-DEU GUI adopts the flow metaphor with visual aids to simplify developing applications by allowing step-by-step rule definitions. As part of the experimentation, AmI-DEU includes a testbed for IoT application development. Experimental results show a potential semantic optimization for dynamic IoT applications in smart homes and smart cities. Our approach promotes technology adoption to improve people’s well-being and quality of life. This thesis concludes with research directions that the AmI-DEU framework uncovers to achieve pervasive smart environments providing suitable adaptations to support people’s intentions
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