http://dspace.univ-chlef.dz/handle/123456789/347 Université Hassiba Benbouali de Chlef / Faculté des sciences 2026-04-30T12:31:40Z http://dspace.univ-chlef.dz/handle/123456789/2429 On certain boundary value problems involving fractional-order differential equations BOUZID, Houari This thesis presents several results on the existence, uniqueness, and stability of nonlocal and boundary value problems for differential equations involving the generalized Caputo fractional derivatives. In addition, we investigate coupled systems of nonlinear fractional differential equations within the same framework. The analysis relies on fixed point theorems, including those of Krasnoselskii, Dhage, Schaefer, and the Banach contraction principle. Moreover, the study extends to Banach spaces, employing Darbo’s fixed-point theorem in conjunction with the measure of noncompactness technique. Each chapter is considered a continuation of the previous one and ends with illustrations to show the applicability of the results. 2026-01-01T00:00:00Z http://dspace.univ-chlef.dz/handle/123456789/2412 Predictive approaches to the impact of environmental conditions on the durability of clayey soils stabilized with mineral additives. TOUALBIA, YOUSSOUF This doctoral thesis addresses a critical issue in geotechnical engineering: the impact of environmental conditions, particularly freeze–thaw cycles, on the effectiveness and long-term durability of stabilized clayey soils treated with mineral additives such as lime and fly ash. Numerous published experimental studies have demonstrated an initial improvement in unconfined compressive strength (UCS) following stabilization, but also a progressive deterioration of mechanical performance under repeated freeze–thaw exposure. However, experimental assessment remains challenging, due to the difficulty in realistically reproducing climatic conditions, precisely controlling curing parameters, and managing result variability. These limitations justify the adoption of predictive modeling approaches. In this context, two modeling approaches: a statistical regression and an ANN, were developed using literature-based experimental databases for soils stabilized with lime and fly ash. These models effectively simulate the evolution of UCS in stabilized soils subjected to environmental cycles. Parametric studies were also conducted to capture the influence of several key factors, such as the number of freeze–thaw cycles, water content, additive content, and curing duration. Results show that ANN models offer superior predictive performance and better capture of nonlinear relationships between input variables and soil strength response. By integrating diverse experimental data and leveraging the power of artificial intelligence, this work contributes to a better understanding of the long-term behavior of stabilized soils under harsh climatic conditions and provides reliable tools to support resilient geotechnical design in environmentally sensitive regions. Keywords: stabilized clayey soils; freeze–thaw cycles; mineral additives; statistical model; artificial neural network (ANN); unconfined compressive strength (UCS) THESIS Submitted for the DOCTORAL DEGREE Field: Civil Engineering Specialty: Geotechnical Engineering 2025-01-01T00:00:00Z http://dspace.univ-chlef.dz/handle/123456789/2411 A task classification strategy for IoT/Cloud collaboration BENABOURA, AMINA There is a growing need for efficient computational offloading technologies that can handle large data flows while adhering to strict response time and power consumption constraints as a result of the explosive growth of Internet of Things (IoT) devices. Real-time IoT applications require scalability and responsiveness, which traditional cloud computing cannot provide. To address these issues, this thesis presents a task offloading framework based on Deep Q-Network (DQN) in a collaborative architecture between IoT, fog computing, and cloud computing levels for intelligent and adaptive decision-making that maximizes system performance. The DQNbased strategy achieves superior performance, with reductions of up to 50% in total cost, 33% in latency, and 25% in energy consumption compared to competing methods, according to extensive simulation experiments against state-of-the-art algorithms, such as bat, DJA, and DDPG-based approaches. The DQN algorithm also shows strong convergence behavior, low variance, and high reliability across multiple scenarios, confirming its robustness and adaptability in distributed computing environments. In order to improve Quality of Service (QoS) and Quality of Experience (QoE) in IoT–fog–cloud ecosystems, this work offers a scalable, data-driven offloading solution, which advances the expanding field of intelligent task management. The suggested framework opens perspectives for more independent and energy-conscious computing paradigms by laying the groundwork for future studies on multiagent deep reinforcement learning, federated offloading techniques, and optical network-enhanced IoT infrastructures. THESIS Submitted in partial fulfillment of the requirements for the degree of DOCTORATE Field: Computer Science Specialization: Artificial Intelligence and Software Engineering 2026-01-01T00:00:00Z http://dspace.univ-chlef.dz/handle/123456789/2217 Design and implementation of a secure LoRaWAN protocol used in critical applications in the IoT domain Abdelouahab, Nouar Of the available wireless transmission technologies, LPWANs (Low Power Wide Area Networks) are attracting increasing attention, not least because of their long radio range and low energy consumption. However, trying to minimize power consumption can sometimes compromise the resilience of data transmission in the face of environmental disturbances (interference, obstacles) and the mobility of connected objects. However, attempting to reduce power consumption can occasionally compromise the mobility of linked items and the robustness of data transmission against environmental disruptions (obstacles, interference). Additionally, each node’s duration occupancy of the frequency band is limited by the long radio range (e.g. duty cycle limited to 1%). We concentrate on LoRa/LoRaWAN technologies in this thesis. LoRaWAN may be able to accommodate a wide range of IoT applications and situations because to its numerous adjustable characteristics. It can converge to an ideal configuration to save energy due to its ADR (Adaptive Data Rate) function. More recently, LoRa and LoRaWAN have also drawn interest from applications utilizing mobile nodes. This thesis’s first contribution is its presentation of how mobility affects LoRaWAN performance. To achieve this, the research consists of two (02) parts: In the first part, we present an in-depth analysis of LoRaWAN performance evaluation in a mobility context. To do this, we consider several scenarios and performance evaluation measures using the NS − 3 simulator, based on the three mobility models most widely used in the literature, such as the Gauss Markov Mobility Model, the Random Waypoint Mobility model and the Constant Position Mobility Model. The new study presents the influence of these three models on energy consumption, PDR, network size and Radius. In order to validate the simulation results, in the second part we carried out numerous experiments with the Lora CubeCell HTCC-AB01 in various scenarios, analyzing the RSSI (Received Signal Strength Indicator) level in urban and rural areas using a large number of trajectories. The maximum distance obtained in a rural area is 1310 meters of line of sight, while in an urban area, the distance is equal to 966.97 meters of line of sight. In terms of energy consumption, the results show that the GM model is 0.1 J, and for the RWP and CP it is 0.4 J, which equals 9.6 J in 24 hours, which makes the GM model four times more efficient. The GM model with Alpha = 1 performs better than the other two models, and Alpha = 0.5 performs even better in terms of PDR. At the same time, the RWP demonstrates positive results regarding delays. In order to find the best combination for packet transmission, we provide a second contribution in this thesis to the description of the SFs allocation scheme for Lorawan. Furthermore, even though the various simulations carried out and the results obtained, we consider it more appropriate to use mathematical and logical methods to validate the ADR mechanism, and this was the subject of our third contribution. We used Event-B (the formal method) to model the protocol layers and their properties, and Event-B invariants to ensure protocol consistency, and we’ll add more guarantees to the validity of the protocol, focusing on the formal validation of the ADR mechanism on the network server side. The security aspect is studied, by presenting the physical structure of Lora packet, the Mac message types and the different LoraWan Mac commands, followed by the two activation modes of Lora End Devices including OTAA and ABP Mode. In all the literature, to our knowledge, currently the deployment of cryptography using the NS-3 simulator has not yet achieved, this is the subject of our main and last contribution, our goal is the implementation of AES-128 bits algorithm under the NS-3 simulator, and to assess the performance of the LoRaWAN network in terms of energy consumption, transmission latency, packet delivery rate, and CPU utilization. The findings indicate a shift in the transmission delay from 0.25 ms to 1.7 ms for a packet of 12 bytes and 216 bytes respectively 2025-01-01T00:00:00Z