Doctorat
Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/59
Browse
3 results
Search Results
Item Coordination of scout drones (UAVs) in smart-city to serve autonomous vehicles(Université M'Hamed Bougara Boumerdès : Faculté de Technologie, 2023) Ait Saadi, Amylia; Meraihi, Yassine(Directeur de thèse); Ramdane-Cherif, Amar(Directeur de thèse)The subject of Unmanned Aerial Vehicles (UAVs) has become a promising study field in both research and industry. Due to their autonomy and efficiency in flight, UAVs are considerably used in various applications for different tasks. Actually, the autonomy of the UAV is a challenging issue that can impact both its performance and safety during the mission. During the flight, the autonomous UAVs are required to investigate the area and determine efficiently their trajectory by preserving their resources (energy related to both altitude and path length) and satisfying some constraints (obstacles and axe rotations). This problem is defined as the UAV path planning problem that requires efficient algorithms to be solved, often Artificial Intelligence algorithms. In this thesis, we present two novel approaches for solving the UAV path planning problem. The first approach is an improved algorithm based on African Vultures Optimization Algorithm (AVOA), called CCO-AVOA algorithms, which integrates the Chaotic map, Cauchy mutation, and Elite Opposition-based learning strategies. These three strategies improve the performance of the original AVOA algorithm in terms of the diversity of solutions and the exploration/exploitation search balance. A second approach is a hybrid-based approach, called CAOSA, based on the hybridization of Chaotic Aquila Optimization with Simulated Annealing algorithms. The introduction of the haotic map enhances the diversity of the Aquila Optimization (AO), while the Simulated Annealing (SA) algorithm is applied as a local search algorithm to improve the exploitation search of the traditional AO algorithm. Finally, the autonomy and efficiency of the UAV are tackled in another important application, which is the UAV placement problem. The issue of the UAV placement relays on finding the optimal UAV placement that satisfies both the network coverage and connectivity while considering the UAV’s limitation from energy and load. In this context, we proposed an efficient hybrid called IMRFO-TS, based on the combination of Improved Manta Ray Foraging Optimization, which integrates a tangential control strategy and Tabu Search algorithmsItem Optimization of wireless mesh networks planning(Université M'Hamed Bougara : Faculté de Technologie, 2023) Mekhmoukh, Sylia; Meraihi, Yassine(Directeur de thèse)The main challenge in Wireless Mesh Networks (WMNs) is the deployment issue that has a significant impact on the performance of such networks (coverage, connectivity, load balancing, and throughput), cost, and the capacity to satisfy the Quality of service requirements. In the context of mesh routers placement, the performance of the network is influenced by the number and locations of mesh router, the transmission range of each mesh router, the number of covered clients per mesh router, the size of the deployment area, and the number and weights of mesh clients. The mesh routers placement problem is an NPhard optimization problem, successfully solved using meta-heuristic optimization approaches with reasonable time execution. In this work, we propose three approaches for solving the mesh routers placement problem. The first approach is an improved version of Moth Flame Optimization (MFO), called ECLO-MFO, based on the integration of three strategies including: the Lévy Flight Distribution (LFD) strategy, chaotic map, and the Opposition Based-Learning (OBL) technique to enhance the optimization performance of MFO. The second approach is a hybrid approach, called ASO-SA, based on the combination of global search capability of an Adaptive Snake Optimizer (ASO) with the local search capability of Simulated Annealing (SA). ASO is based on the integration of the Generalized OBL (GOBL) mechanism into the exploration phase of SO. Finally a Binary Whale Optimization Algorithm (BWOA) is suggested to solve the topology planning problem in WMNs. Eight transfer functions divided into two families such as S-shaped and V-shaped are introduced and analyzed to obtain a binary version of WOAItem Improvement of vlc technology and deployment in the context of smart city(Université M'Hamed Bougara : Faculté de Technologie, 2023) Yahia, Selma; Meraihi, Yassine(Directeur de thèse)The demand for wireless communication systems has increased dramatically due to their ability to enable the exchange of information between various devices, o?ering the potential to enhance safety, manage tra?c and improve convenience. Extensive research and standardization e?orts in wireless communications have focused on radio frequency (RF) technologies. Nevertheless, RF technologies are susceptible to high levels of interference and channel congestion in heavily populated areas, which can adversely a?ect the performance of delay-sensitive applications. To mitigate such problems, researchers from academia and industry started to explore and develop new communication technologies. Visible light communication (VLC) is considered one of the promising technologies. VLC uses the visible part of the electromagnetic spectrum and o?ers an alternative solution to the limitations posed by RF communications. The data transmission through VLC technology depends on the ability to modulate the intensity of the Light-Emitting-Diode (LED), enabling the dual use of LED for illumination and communication purposes. This results in a highly e?cient, low-power, and low-latency communication solution, that is immune to interference from other communication technologies. VLC deploys the existing lighting infrastructures, which o?ers an innovative way to transmit data in widespread areas and for various applications such as indoor communication, vehicular communications, and smart cities. VLC is still new in some applications and requires extensive e?orts to cope with several challenges in di?erent aspects, including system and channel modeling, transceiver modeling and design, optimization of various system parameters, and performance analysis. This thesis provides a comprehensive study of di?erent research topics in VLC technology. The objective is to shed light on the new applications of VLC systems, illustrating the challenges that limit the system performance and introducing novel solutions to improve such performance. In the ?rst part of this dissertation, we provide a comprehensive review of VLC technology, illustrating the existing research e?orts on di?erent prospects. That starts from the system and channel modeling and reaches the performance analysis and system implemen- III ABSTRACT tation. Since channel modeling is critical for system design and performance estimation, we then focus on that and present a comprehensive study of the traditional and advanced channel modeling approaches for VLC systems. We illustrate the advantages and the capabilities of utilizing the advanced non-sequential ray tracing channel modeling approach. These include the ability to incorporate and model practical and commercial light sources with their di?erent radiation patterns and the consideration of many re?ections to provide more accurate results. Therefore, we adopt this channel modeling approach, which forms the foundation of our research, to model and evaluates the performance of di?erent VLC applications and scenarios in the other parts of the thesis. Our work focuses primarily on improving the performance and e?ciency of VLC systems in indoor and outdoor applications. In the second part of this thesis, we consider the outdoor scenarios aiming to improve the system performance through novel receiver designs, including imaging and non-imaging receivers. Utilizing the proposed structure, we investigate the performance of both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) VLC applications. The third part of this thesis focuses on indoor applications where a novel resource allocation scheme is proposed to enhance the performance of Massive Optical internetof-things (IoT) systems. The proposed technique depends on an improved version of the Aquila Optimization (AO) algorithm, which integrates chaotic maps, Quasi-OppositionBased Learning (QOBL) concept, Fitness-distance balance (FDB) selection methods, and cosine functions into the original AO algorithm to enhance its performance. Extensive simulations and analyses are conducted to compare the system performance using the proposed designs, algorithms, and schemes with the existing literature work. The results demonstrate the e?ectiveness of our proposed work in improving the performance and e?ciency of the VLC system in indoor and outdoor scenarios. To conclude, this dissertation provides a comprehensive study of VLC technology, o?ering new insights into system and channel modeling, receiver design, transmission schemes, and system optimization, paving the way for future research extensions in this area