Performance Evolution in Satellite Communication Networks Along with Markovian Channel Prediction

Abstract Augmenting accurate predict ion of channel attenuations can be of immense value in improving the quality of signals athigh frequency for satellite co mmunication networks. Such prediction of weather related attenuation factors for the impendingweather conditions based on the weather data and the Markovian theory are the main object of this paper. The paper also describes anintelligent weather aware control system (IWACS) that is used to emp loy the predict ions made fro m Markov model to maintainthe quality of service (QoS) in channels that are impacted by rain, gaseous, cloud, fog, and scintillat ion attenuations. Based onthat, a three dimensional relationship is proposed among estimated at mospheric attenuations, propagation angle, and predictedrainfall rate (RR pr ) at a given location and operational frequency. This novel method of pred icting weather characteristicssupplies valuable data for mit igation planning, and subsequently for developing an algorithm to iteratively tune the IWACS byadaptively selecting appropriate channel frequency, modulation, coding, propagation angle, transmission power level, and datatransmission rate to imp rove the satellite's system performance. So me simulat ion results are presented to show the effectiveness of the proposedscheme

Robust Controller for Delays and Packet Dropout Avoidance in Solar-Power Wireless Network

Solar Wireless Networked Control Systems (SWNCS) are a style of distributed control systems where sensors, actuators, and controllers are interconnected via a wireless communication network. This system setup has the benefit of low cost, flexibility, low weight, no wiring and simplicity of system diagnoses and maintenance. However, it also unavoidably calls some wireless network time delays and packet dropout into the design procedure. Solar lighting system offers a clean environment, therefore able to continue for a long period. SWNCS also offers multi Service infrastructure solution for both developed and undeveloped countries. The system provides wireless controller lighting, wireless communications network (WI-FI/WIMAX), CCTV surveillance, and wireless sensor for weather measurement which are all powered by solar energy

Enhancing infotainment applications quality of service in vehicular ad hoc networks

Les réseaux ad hoc de véhicules accueillent une multitude d’applications intéressantes. Parmi celles-ci, les applications d’info-divertissement visent à améliorer l’expérience des passagers. Ces applications ont des exigences rigides en termes de délai de livraison et de débit. De nombreuses approches ont été proposées pour assurer la qualité du service des dites applications. Elles sont réparties en deux couches : réseau et contrôle d’accès. Toutefois, ces méthodes présentent plusieurs lacunes. Cette thèse a trois volets. Le premier aborde la question du routage dans le milieu urbain. A cet égard, un nouveau protocole, appelé SCRP, a été proposé. Il exploite l’information sur la circulation des véhicules en temps réel pour créer des épines dorsales sur les routes et les connecter aux intersections à l’aide des nœuds de pont. Ces derniers collectent des informations concernant la connectivité et le délai, utilisées pour choisir les chemins de routage ayant un délai de bout-en-bout faible. Le deuxième s’attaque au problème d’affectation des canaux de services afin d’augmenter le débit. A cet effet, un nouveau mécanisme, appelé ASSCH, a été conçu. ASSCH collecte des informations sur les canaux en temps réel et les donne à un modèle stochastique afin de prédire leurs états dans l’avenir. Les canaux les moins encombrés sont sélectionnés pour être utilisés. Le dernier volet vise à proposer un modèle analytique pour examiner la performance du mécanisme EDCA de la norme IEEE 802.11p. Ce modèle tient en compte plusieurs facteurs, dont l’opportunité de transmission, non exploitée dans IEEE 802.11p.The fact that vehicular ad hoc network accommodates two types of communications, Vehicle-to-Vehicle and Vehicle-to-Infrastructure, has opened the door for a plethora of interesting applications to thrive. Some of these applications, known as infotainment applications, focus on enhancing the passengers' experience. They have rigid requirements in terms of delivery delay and throughput. Numerous approaches have been proposed, at medium access control and routing layers, to enhance the quality of service of such applications. However, existing schemes have several shortcomings. Subsequently, the design of new and efficient approaches is vital for the proper functioning of infotainment applications. This work proposes three schemes. The first is a novel routing protocol, labeled SCRP. It leverages real-time vehicular traffic information to create backbones over road segments and connect them at intersections using bridge nodes. These nodes are responsible for collecting connectivity and delay information, which are used to select routing paths with low end-to-end delay. The second is an altruistic service channel selection scheme, labeled ASSCH. It first collects real-time service channels information and feeds it to a stochastic model that predicts the state of these channels in the near future. The least congested channels are then selected to be used. The third is an analytical model for the performance of the IEEE 802.11p Enhanced Distributed Channel Access mechanism that considers various factors, including the transmission opportunity (TXOP), unexploited by IEEE 802.11p

Task-Driven Integrity Assessment and Control for Vehicular Hybrid Localization Systems

Throughout the last decade, vehicle localization has been attracting significant attention in a wide range of applications, including Navigation Systems, Road Tolling, Smart Parking, and Collision Avoidance. To deliver on their requirements, these applications need specific localization accuracy. However, current localization techniques lack the required accuracy, especially for mission critical applications. Although various approaches for improving localization accuracy have been reported in the literature, there is still a need for more efficient and more effective measures that can ascribe some level of accuracy to the localization process. These measures will enable localization systems to manage the localization process and resources so as to achieve the highest accuracy possible, and to mitigate the impact of inadequate accuracy on the target application. In this thesis, a framework for fusing different localization techniques is introduced in order to estimate the location of a vehicle along with location integrity assessment that captures the impact of the measurement conditions on the localization quality. Knowledge about estimate integrity allows the system to plan the use of its localization resources so as to match the target accuracy of the application. The framework introduced provides the tools that would allow for modeling the impact of the operation conditions on estimate accuracy and integrity, as such it enables more robust system performance in three steps. First, localization system parameters are utilized to contrive a feature space that constitutes probable accuracy classes. Due to the strong overlap among accuracy classes in the feature space, a hierarchical classification strategy is developed to address the class ambiguity problem via the class unfolding approach (HCCU). HCCU strategy is proven to be superior with respect to other hierarchical configuration. Furthermore, a Context Based Accuracy Classification (CBAC) algorithm is introduced to enhance the performance of the classification process. In this algorithm, knowledge about the surrounding environment is utilized to optimize classification performance as a function of the observation conditions. Second, a task-driven integrity (TDI) model is developed to enable the applications modules to be aware of the trust level of the localization output. Typically, this trust level functions in the measurement conditions; therefore, the TDI model monitors specific parameter(s) in the localization technique and, accordingly, infers the impact of the change in the environmental conditions on the quality of the localization process. A generalized TDI solution is also introduced to handle the cases where sufficient information about the sensing parameters is unavailable. Finally, the produce of the employed localization techniques (i.e., location estimates, accuracy, and integrity level assessment) needs to be fused. Nevertheless, these techniques are hybrid and their pieces of information are conflicting in many situations. Therefore, a novel evidence structure model called Spatial Evidence Structure Model (SESM) is developed and used in constructing a frame of discernment comprising discretized spatial data. SESM-based fusion paradigms are capable of performing a fusion process using the information provided by the techniques employed. Both the location estimate accuracy and aggregated integrity resultant from the fusion process demonstrate superiority over the employing localization techniques. Furthermore, a context aware task-driven resource allocation mechanism is developed to manage the fusion process. The main objective of this mechanism is to optimize the usage of system resources and achieve a task-driven performance. Extensive experimental work is conducted on real-life and simulated data to validate models developed in this thesis. It is evident from the experimental results that task-driven integrity assessment and control is applicable and effective on hybrid localization systems