Pervasive computing implies the invisibility of the technology involved in providing ubiquity, such that technology is integrated into the environment and non-intrusive. In such a manner, computing and networking resources become diffused into physical environments, enabling users to exploit their provided functionalities such that functionality is distributed, enabling it to be controlled, monitored, managed, and extended beyond what it was initially designed to do. Moreover, computer awareness moves towards user-centricity, whereby systems seamlessly adapt to the characteristics, preferences, and current situations of users and their respective surrounding environments. Users exploit such functionalities in the form of a virtual device, whereby a collection of heterogeneous devices in the vicinity of the user are behaving as one single homogeneous device for the benefit of the user in solving some given task. This dissertation investigates the problem of dynamic composition and management of virtual devices for ad hoc multimedia service delivery and proposes an autonomous policy driven framework for virtual device management. The framework consists of a hierarchical structure of distributed elements, including autonomic elements, all working towards the self-management of virtual devices. The research presented in this dissertation addresses the functionalities of these components. More specifically, contributions are made towards the autonomous management of virtual devices, moving away from infrastructure based schemes with heavy user involvement to decentralized and zero touch (i.e., no user involvement) solutions. In doing so, the components and methodology behind a policy-driven autonomous framework for the dynamic discovery, selection, and composition of multimodal multi-device services are presented. The framework operates in an ad hoc network setting and introduces a Service Overlay Network (SON) based definition of a virtual device. Furthermore, device and service discovery, composition, integration, and adaptation schemes are designed for Mobile Ad hoc Network Environments (MANETs) enabling users to generate, on-the-fly, complex strong specific systems, embedding in a distributed manner, QoS models providing compositions that form the best possible virtual device at the time of need. Experimental studies are presented to demonstrate the performance of the proposed schemes.

Pervasive computing implies the invisibility of the technology involved in providing ubiquity, such that technology is integrated into the environment and non-intrusive. In such a manner, computing and networking resources become diffused into physical environments, enabling users to exploit their provided functionalities such that functionality is distributed, enabling it to be controlled, monitored, managed, and extended beyond what it was initially designed to do. Moreover, computer awareness moves towards user-centricity, whereby systems seamlessly adapt to the characteristics, preferences, and current situations of users and their respective surrounding environments. Users exploit such functionalities in the form of a virtual device, whereby a collection of heterogeneous devices in the vicinity of the user are behaving as one single homogeneous device for the benefit of the user in solving some given task. This dissertation investigates the problem of dynamic composition and management of virtual devices for ad hoc multimedia service delivery and proposes an autonomous policy driven framework for virtual device management. The framework consists of a hierarchical structure of distributed elements, including autonomic elements, all working towards the self-management of virtual devices. The research presented in this dissertation addresses the functionalities of these components. More specifically, contributions are made towards the autonomous management of virtual devices, moving away from infrastructure based schemes with heavy user involvement to decentralized and zero touch (i.e., no user involvement) solutions. In doing so, the components and methodology behind a policy-driven autonomous framework for the dynamic discovery, selection, and composition of multimodal multi-device services are presented. The framework operates in an ad hoc network setting and introduces a Service Overlay Network (SON) based definition of a virtual device. Furthermore, device and service discovery, composition, integration, and adaptation schemes are designed for Mobile Ad hoc Network Environments (MANETs) enabling users to generate, on-the-fly, complex strong specific systems, embedding in a distributed manner, QoS models providing compositions that form the best possible virtual device at the time of need. Experimental studies are presented to demonstrate the performance of the proposed schemes.

Pervasive computing implies the invisibility of the technology involved in providing ubiquity, such that technology is integrated into the environment and non-intrusive. In such a manner, computing and networking resources become diffused into physical environments, enabling users to exploit their provided functionalities such that functionality is distributed, enabling it to be controlled, monitored, managed, and extended beyond what it was initially designed to do. Moreover, computer awareness moves towards user-centricity, whereby systems seamlessly adapt to the characteristics, preferences, and current situations of users and their respective surrounding environments. Users exploit such functionalities in the form of a virtual device, whereby a collection of heterogeneous devices in the vicinity of the user are behaving as one single homogeneous device for the benefit of the user in solving some given task. This dissertation investigates the problem of dynamic composition and management of virtual devices for ad hoc multimedia service delivery and proposes an autonomous policy driven framework for virtual device management. The framework consists of a hierarchical structure of distributed elements, including autonomic elements, all working towards the self-management of virtual devices. The research presented in this dissertation addresses the functionalities of these components. More specifically, contributions are made towards the autonomous management of virtual devices, moving away from infrastructure based schemes with heavy user involvement to decentralized and zero touch (i.e., no user involvement) solutions. In doing so, the components and methodology behind a policy-driven autonomous framework for the dynamic discovery, selection, and composition of multimodal multi-device services are presented. The framework operates in an ad hoc network setting and introduces a Service Overlay Network (SON) based definition of a virtual device. Furthermore, device and service discovery, composition, integration, and adaptation schemes are designed for Mobile Ad hoc Network Environments (MANETs) enabling users to generate, on-the-fly, complex strong specific systems, embedding in a distributed manner, QoS models providing compositions that form the best possible virtual device at the time of need. Experimental studies are presented to demonstrate the performance of the proposed schemes.

Pervasive computing implies the invisibility of the technology involved in providing ubiquity, such that technology is integrated into the environment and non-intrusive. In such a manner, computing and networking resources become diffused into physical environments, enabling users to exploit their provided functionalities such that functionality is distributed, enabling it to be controlled, monitored, managed, and extended beyond what it was initially designed to do. Moreover, computer awareness moves towards user-centricity, whereby systems seamlessly adapt to the characteristics, preferences, and current situations of users and their respective surrounding environments. Users exploit such functionalities in the form of a virtual device, whereby a collection of heterogeneous devices in the vicinity of the user are behaving as one single homogeneous device for the benefit of the user in solving some given task. This dissertation investigates the problem of dynamic composition and management of virtual devices for ad hoc multimedia service delivery and proposes an autonomous policy driven framework for virtual device management. The framework consists of a hierarchical structure of distributed elements, including autonomic elements, all working towards the self-management of virtual devices. The research presented in this dissertation addresses the functionalities of these components. More specifically, contributions are made towards the autonomous management of virtual devices, moving away from infrastructure based schemes with heavy user involvement to decentralized and zero touch (i.e., no user involvement) solutions. In doing so, the components and methodology behind a policy-driven autonomous framework for the dynamic discovery, selection, and composition of multimodal multi-device services are presented. The framework operates in an ad hoc network setting and introduces a Service Overlay Network (SON) based definition of a virtual device. Furthermore, device and service discovery, composition, integration, and adaptation schemes are designed for Mobile Ad hoc Network Environments (MANETs) enabling users to generate, on-the-fly, complex strong specific systems, embedding in a distributed manner, QoS models providing compositions that form the best possible virtual device at the time of need. Experimental studies are presented to demonstrate the performance of the proposed schemes.

No description available.

Since the ability of Workforce Management Systems to handle mobility induced challenges of mobile environments like data-communication cut-offs, reduced network bandwidth, and security concerns improved recently, the optimization efforts of mobile enterprises increasingly focus on the organizational setup of their mobile environment. This includes issues like, e.g., the dimension and staffing of regional subdivisions, qualification balance of the workforce, and resource allocation strategies. While this multitude of possible adjustment parameters for optimization prevents from the analytical prediction of organizational change efforts, simulation is a promising approach to analyze mobile environments and their change. In this work we present a formal model representing a generalization of mobile environments. This model can be utilized to examine the cost situation and performance of both real mobile enterprises and projected future development scenarios of such enterprises. The model is developed using colored petri nets (CPN) and the software suite CPN Tools. We show that our model is capable of predicting the outcomes of organizational change projects by the utilization of simulation and present a validation of our model based on real-world data of a German gas and power supply.

To support video communication over mobile environments has been one of the objectives of many engineers of telecommunication networks and it has become a basic requirement of a third generation of mobile communication systems. This dissertation explores the possibility of optimizing the utilization of shared scarce radio channels for live video transmission over a GSM (Global System for Mobile telecommunications) network and realizing error resilient video communication in unfavorable channel conditions, especially in mobile radio channels. The main contribution describes the adoption of a SEC (Second Error Correction) approach using ECC (Error Correction Coding) based on a Punctured Convolutional Coding scheme, to cope with residual errors at the application layer and enhance the error resilience of a compressed video bitstream. The approach is developed further for improved performance in different circumstances, with some additional enhancements involving Intra Frame Relay and Interleaving, and the combination of the approach with Packetization. Simulation results of applying the various techniques to test video sequences Akiyo and Salesman are presented and analyzed for performance comparisons with conventional video coding standard. The proposed approach shows consistent improvements under these conditions. For instance, to cope with random residual errors, the simulation results show that when the residual BER (Bit Error Rate) reaches 10-4, the video output reconstructed from a video bitstream protected using the standard resynchronization approach is of unacceptable quality, while the proposed scheme can deliver a video output which is absolutely error free in a more efficient way. When the residual BER reaches 10-3, the standard approach fails to deliver a recognizable video output, while the SEC scheme can still correct all the residual errors with modest bit rate increase. In bursty residual error conditions, the proposed scheme also outperforms the resynchronization approach. Future works to extend the scope and applicability of the research are suggested in the last chapter of the thesis.

La combinaison de données multi-capteurs joue un rôle croissant dans les systèmes de percep- tion artificielle. Les données de profondeur et les capteurs LiDAR en particulier sont devenus la norme pour les systèmes de vision dans les applications de robotique et de conduite auto- nome. La fusion de capteurs peut améliorer la précision des tâches et a été largement étudiée dans des environnements à ressources élevées, mais elle est moins bien comprise dans les ap- plications où les systèmes peuvent être limités en termes de puissance de calcul et de stockage d’énérgie. Dans l’analyse de la démarche chez l’homme, la compréhension du contexte local de la marche joue un rôle important, et l’analyse en laboratoire à elle même peut limiter la capacité des chercheurs à évaluer correctement la marche réelle des patients. La capacité de classifier automatiquement les terrains de marche dans divers environnements pourrait donc constituer un élément important des systèmes d’analyse de l’activité de marche. Le ter- rain de marche peut être mieux identifié à partir de données visuelles. Plusieurs contraintes (notamment les problèmes de confidentialité liés à l’envoi de données visuelles en temps réel hors appareil) limitent cette tâche de classification au dispositif Edge Computing lui- même, un environnement aux ressources limitées. Ainsi, dans ce travail, nous présentons une architecture de réseau neuronal convolutif parallèle, à fusion tardive et optimisée par calcul de bord pour l’identification des terrains de marche. L’analyse est effectuée sur un nouvel ensemble de données intitulé L-AVATeD: l’ensemble de données Lidar et visibles de terrain de marche, composé d’environ 8000 paires de données de scène visuelles (RVB) et de profondeur (LiDAR). Alors que les modèles formés sur des données visuelles uniquement produisent un modèle de calcul de bord capable d’une précision de 82%, une architecture composée d’instances parallèles de MobileNetV2 utilisant à la fois RVB et LiDAR améliore de manière mesurable la précision de la classification (92%) / Terrain classification is a critical sub-task of many autonomous robotic control processes and important to the study of human gait in ecological contexts. Real-time terrain iden- tification is traditionally performed using computer vision systems with input from visual (camera) data. With the increasing availability of affordable multi-sensor arrays, multi- modal data inputs are becoming ubiquitous in mobile, edge and Internet of Things (IoT) devices. Combinations of multi-sensor data therefore play an increasingly important role in artificial perception systems. Depth data in general and LiDAR sensors in particular are becoming standard for vision systems in applications in robotics and autonomous driving. Sensor fusion using depth data can enhance perception task accuracy and has been widely studied in high resource environments (e.g. autonomous automobiles), but is less well understood in applications where resources may be limited in compute, memory and battery power. An understanding of local walking context also plays an important role in the analysis of gait in humans, and laboratory analysis of on its own can constrain the ability of researchers to properly assess real-world gait in patients. The ability to automatically classify walking terrain in diverse environments is therefore an important part of gait analysis systems for use outside the laboratory. Several important constraints (notably privacy concerns associated with sending real-time image data off-device) restrict this classification task to the edge- computing device, itself a resource-constrained environment. In this study, we therefore present an edge-computation optimized, late-fusion, parallel Convolutional Neural Network (CNN) architecture for the real-time identification of walking terrain. Our analysis is performed on a novel dataset entitled L-AVATeD: the Lidar And Visible wAlking Terrain Dataset, consisting of approximately 8,000 pairs of visual (RGB) and depth (LiDAR) scene data. While simple models trained on visual only data produce an edge-computation model capable of 82% accuracy, an architecture composed of parallel instances of MobileNetV2 using both RGB and LiDAR data, measurably improved classifi- cation accuracy (92%).