4,049 research outputs found

    Context Aware Computing for The Internet of Things: A Survey

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    As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

    Hybrid Architecture to Support Context‐Aware Systems

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    Any system that is said to be context‐aware is capable of monitoring continuously the surrounding environment, that is, capable of prompt reaction to events and changing conditions of the environment. The main objective of a context‐aware system is to be continuously recognizing the state of the environment and the users present, in order to adjust the environment to an ideal state and to provide personalized information and services to users considering the user profile. In this chapter, we describe an architecture that relies on the incorporation of intelligent multi‐agent systems (MAS), sensor networks, mobile sensors, actuators, Web services and ontologies. We describe the interaction of these technologies into the architecture aiming at facilitating the construction of context‐aware systems

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

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    Cette thĂšse vise Ă  Ă©tendre l’utilisation de l'Internet des objets (IdO) en facilitant le dĂ©veloppement d’applications par des personnes non experts en dĂ©veloppement logiciel. La thĂšse propose une nouvelle approche pour augmenter la sĂ©mantique des applications d’IdO et l’implication des experts du domaine dans le dĂ©veloppement d’applications sensibles au contexte. Notre approche permet de gĂ©rer le contexte changeant de l’environnement et de gĂ©nĂ©rer des applications qui s’exĂ©cutent dans plusieurs environnements intelligents pour fournir des actions requises dans divers contextes. Notre approche est mise en Ɠuvre dans un cadriciel (AmI-DEU) qui inclut les composants pour le dĂ©veloppement d’applications IdO. AmI-DEU intĂšgre les services d’environnement, favorise l’interaction de l’utilisateur et fournit les moyens de reprĂ©senter le domaine d’application, le profil de l’utilisateur et les intentions de l’utilisateur. Le cadriciel permet la dĂ©finition d’applications IoT avec une intention d’activitĂ© autodĂ©crite qui contient les connaissances requises pour rĂ©aliser l’activitĂ©. Ensuite, le cadriciel gĂ©nĂšre Intention as a Context (IaaC), qui comprend une intention d’activitĂ© autodĂ©crite avec des connaissances colligĂ©es Ă  Ă©valuer pour une meilleure adaptation dans des environnements intelligents. La sĂ©mantique de l’AmI-DEU est basĂ©e 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 rĂšgles et l'appariement sĂ©mantique pour produire des applications IdO autonomes capables de s’exĂ©cuter en ContextAA. AmI- DEU inclut Ă©galement un outil de dĂ©veloppement visuel pour le dĂ©veloppement et le dĂ©ploiement rapide d'applications sur ContextAA. L'interface graphique d’AmI-DEU adopte la mĂ©taphore du flux avec des aides visuelles pour simplifier le dĂ©veloppement d'applications en permettant des dĂ©finitions de rĂšgles Ă©tape par Ă©tape. Dans le cadre de l’expĂ©rimentation, AmI-DEU comprend un banc d’essai pour le dĂ©veloppement d’applications IdO. Les rĂ©sultats expĂ©rimentaux montrent une optimisation sĂ©mantique 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 amĂ©liorer le bienĂȘtre et la qualitĂ© de vie des personnes. Cette thĂšse se termine par des orientations de recherche que le cadriciel AmI-DEU dĂ©voile pour rĂ©aliser des environnements intelligents omniprĂ©sents fournissant des adaptations appropriĂ©es 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

    Ubiquitous Computing

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    The aim of this book is to give a treatment of the actively developed domain of Ubiquitous computing. Originally proposed by Mark D. Weiser, the concept of Ubiquitous computing enables a real-time global sensing, context-aware informational retrieval, multi-modal interaction with the user and enhanced visualization capabilities. In effect, Ubiquitous computing environments give extremely new and futuristic abilities to look at and interact with our habitat at any time and from anywhere. In that domain, researchers are confronted with many foundational, technological and engineering issues which were not known before. Detailed cross-disciplinary coverage of these issues is really needed today for further progress and widening of application range. This book collects twelve original works of researchers from eleven countries, which are clustered into four sections: Foundations, Security and Privacy, Integration and Middleware, Practical Applications

    UBIDEV: a homogeneous service framework for pervasive computing environments

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    This dissertation studies the heterogeneity problem of pervasive computing system from the viewpoint of an infrastructure aiming to provide a service-oriented application model. From Distributed System passing through mobile computing, pervasive computing is presented as a step forward in ubiquitous availability of services and proliferation of interacting autonomous entities. To better understand the problems related to the heterogeneous and dynamic nature of pervasive computing environments, we need to analyze the structure of a pervasive computing system from its physical and service dimension. The physical dimension describes the physical environment together wit the technology infrastructure that characterizes the interactions and the relations within the environment; the service dimension represents the services (being them software or not) the environment is able to provide [Nor99]. To better separate the constrains and the functionalities of a pervasive computing system, this dissertation classifies it in terms of resources, context, classification, services, coordination and application. UBIDEV, as the key result of this dissertation, introduces a unified model helping the design and the implementation of applications for heterogeneous and dynamic environments. This model is composed of the following concepts: ‱ Resource: all elements of the environment that are manipulated by the application, they are the atomic abstraction unit of the model. ‱ Context: all information coming from the environment that is used by the application to adapts its behavior. Context contains resources and services and defines their role in the application. ‱ Classification: the environment is classified according to the application ontology in order to ground the generic conceptual model of the application to the specific environment. It defines the basic semantic level of interoperability. ‱ Service: the functionalities supported by the system; each service manipulates one or more resources. Applications are defined as a coordination and adaptation of services. ‱ Coordination: all aspects related to service composition and execution as well as the use of the contextual information are captured by the coordination concept. ‱ Application Ontology: represents the viewpoint of the application on the specific context; it defines the high level semantic of resources, services and context. Applying the design paradigm proposed by UBIDEV, allows to describe applications according to a Service Oriented Architecture[Bie02], and to focus on application functionalities rather than their relations with the physical devices. Keywords: pervasive computing, homogenous environment, service-oriented, heterogeneity problem, coordination model, context model, resource management, service management, application interfaces, ontology, semantic services, interaction logic, description logic.Questa dissertazione studia il problema della eterogeneit`a nei sistemi pervasivi proponendo una infrastruttura basata su un modello orientato ai servizi. I sistemi pervasivi sono presentati come un’evoluzione naturale dei sistemi distribuiti, passando attraverso mobile computing, grazie ad una disponibilit`a ubiqua di servizi (sempre, ovunque ed in qualunque modo) e ad loro e con l’ambiente stesso. Al fine di meglio comprendere i problemi legati allintrinseca eterogeneit`a dei sistemi pervasivi, dobbiamo prima descrivere la struttura fondamentale di questi sistemi classificandoli attraverso la loro dimensione fisica e quella dei loro servizi. La dimensione fisica descrive l’ambiente fisico e tutti i dispositivi che fanno parte del contesto della applicazione. La dimensione dei servizi descrive le funzionalit`a (siano esse software o no) che l’ambiente `e in grado di fornire [Nor99]. I sistemi pervasivi vengono cos`ı classificati attraverso una metrica pi `u formale del tipo risorse, contesto, servizi, coordinazione ed applicazione. UBIDEV, come risultato di questa dissertazione, introduce un modello uniforme per la descrizione e lo sviluppo di applicazioni in ambienti dinamici ed eterogenei. Il modello `e composto dai seguenti concetti di base: ‱ Risorse: gli elementi dell’ambiente fisico che fanno parte del modello dellapplicazione. Questi rappresentano l’unit`a di astrazione atomica di tutto il modello UBIDEV. ‱ Contesto: le informazioni sullo stato dell’ambiente che il sistema utilizza per adattare il comportamento dell’applicazione. Il contesto include informazioni legate alle risorse, ai servizi ed alle relazioni che li legano. ‱ Classificazione: l’ambiente viene classificato sulla base di una ontologia che rappresenta il punto di accordo a cui tutti i moduli di sistema fanno riferimento. Questa classificazione rappresenta il modello concettuale dell’applicazione che si riflette sull’intero ambiente. Si definisce cos`ı la semantica di base per tutto il sistema. ‱ Servizi: le funzionalit`a che il sistema `e in grado di fornire; ogni servizio `e descritto in termini di trasformazione di una o pi `u risorse. Le applicazioni sono cos`ı definite in termini di cooperazione tra servizi autonomi. ‱ Coordinazione: tutti gli aspetti legati alla composizione ed alla esecuzione di servizi cos`ı come l’elaborazione dell’informazione contestuale. ‱ Ontologia dell’Applicazione: rappresenta il punto di vista dell’applicazione; definisce la semantica delle risorse, dei servizi e dell’informazione contestuale. Applicando il paradigma proposto da UBIDEV, si possono descrivere applicazioni in accordo con un modello Service-oriented [Bie02] ed, al tempo stesso, ridurre l’applicazione stessa alle sue funzionalit`a di alto livello senza intervenire troppo su come queste funzionalit` a devono essere realizzate dalle singole componenti fisiche

    NETQOS policy management architecture for flexible QOS provisioning in Future Internet

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    This paper is focussed on the NETQOS architecture for automated QoS policy provisioning, which can be used in Future Internet scenarios by the different actors (i.e. network operators, service providers, and users) for flexible QoS configuration over combinations of mobile, fixed, sensor and broadcast networks. The NETQOS policy management architecture opens the possibility to specify QoS policies on a "business" level using ontology descriptions and policy management interfaces, which are specific to the actors. The business level policy specifications are translated by the NETQOS system into intermediate and operational QoS policies for automated QoS configuration at the managed heterogeneous network and transport entities. NETQOS allows QoS policy specification and dependency analysis considering Service Level Agreements (SLAs) between the actors, as well as automated policy provisioning and adaptation. The interaction of the NETQOS components is based on a common po licy repository. The particular focus of the paper is aimed to discuss ontology and actor oriented QoS policy specification and configuration for heterogeneous networks, as well as NETQOS QoS policy management interfaces at business level and automated translation of business QoS policies to intermediate and operational policy level
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