Publications Internationales

Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/13

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Author: search.filters.author.Meraihi, YassineHas files: Yes

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    An Enhanced Aquila Optimizer Algorithm for Resource Allocation in Indoor Multi-user IoT VLC System
    (2023) Yahia, Selma; Meraihi, Yassine; Mekhmoukh Taleb, Sylia; Mirjalili, Seyedali; Ramdane-Cherif, Amar; B. Eldeeb, Hossien; Muhaidat, Sami
    Visible light communication (VLC) is a rapidly growing wireless communication technology for the Internet of Things (IoT) that offers high data rates and low latency, making it ideal for massive connectivity. Efficient resource allocation is essential in VLC networks to minimize inter-symbol and co- channel interferences, which can greatly improve network perfor- mance and user satisfaction. This paper focuses on an indoor IoT- based VLC system that utilizes photodetectors (PDs) on users’ cell phones as receivers, with the goal of maximizing system performances and reducing power consumption by selectively activating some PDs while deactivating others. However, this objective presents a challenge due to the inherent non-convex nature of the multi-objective optimization problem, which cannot be solved by analytical means. To address this, we propose an enhanced Aquila optimization (EAO) scheme that improves upon the Aquila Optimizer (AO) by incorporating a fitness distance balance (FDB) function. We evaluate our proposed EAO in various scenarios under different settings, considering both capacity and fairness metrics. Through simulations, we demonstrate the effectiveness of our approach and its superiority over classical algorithms such as Aquila Optimizer (AO), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) in finding the optimal solution. Our results confirm that the proposed EAO algorithm can efficiently optimize the system capacity and ensure fairness among all users, providing a promising solution for indoor VLC systems.
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    Performance analysis of bidirectional multi-hop vehicle-to-vehicle visible light communication
    (Institute of Electrical and Electronics Engineers Inc, 2023) Refas, Souad; Acheli, Dalila; Yahia, Selma; Meraihi, Yassine; Ramdane-Cherif, Amar; Van, Nhan Vo; Ho, Tu Dac
    Vehicular visible light communication (VVLC) has emerged as a promising field of research, garnering considerable attention from scientists and researchers. VVLC offers a potential solution to enable connectivity and communication between travelling vehicles along the road by using their existing headlights (HLs) and taillights (TLs) as wireless transmitters and integrating photodetectors (PDs) within the car front or car-back as wireless receivers. However, VVLC encounters more challenges than indoor VLC, particularly in vehicle-to-vehicle (V2V) communication, where vehicle mobility disrupts the establishment of direct communication links. To address this, we propose a multi-hop relay system wherein intermediate vehicles act as wireless relays to maintain a line-of-sight (LoS) link. In this paper, we investigate the performance of a bidirectional multi-hop relay V2V-VLC system that operates in both the forward and backward directions. Based on realistic ray tracing channel models, we derive a closed-form expression for the full bidirectional communication range. We also analyze how the transceiver's parameters and the number of relays affect the system performance. Our results show that the proposed bidirectional multi-hop relay system can extend the direct transmission range by more than 19 m with only a hop relay.
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    A novel hybrid Chaotic Aquila Optimization algorithm with Simulated Annealing for Unmanned Aerial Vehicles path planning
    (Elsevier, 2022) Ait Saadi, Amylia; Meraihi, Yassine; Soukane, Assia; Benmessaoud Gabis, Asma; Amar Ramdane, Cherif
    In recent years, research on Unmanned Aerial Vehicles (UAVs) has become one of the interest- ing topics for industry and academic. UAV path plan- ning is one of the critical issues in terms of guaran- teeing the autonomy and good performance of UAVs in real-world applications. Its main objective is to de- termine and ensure an optimal and collision-free path between two positions from a starting point (source) to a destination one (target) while satisfying some UAV requirements (i.e. UAV’s safety, environment complex- ity, obstacle avoidance, energy consumption,etc). Due to the complexity of this topic, an efficient path plan- ning algorithm is required. This paper presents an opti- mal and hybrid algorithm, called CAOSA, based on the hybridization of Chaotic Aquila Optimization (CAO) and Simulated Annealing (SA) algorithms for solving the UAV path planning problem in a 3D environment. As a first step, chaotic map is introduced to enhance the chaotic stochastic behavior of the Aquila Optimization (AO) algorithm. In the second step, the SA algorithm is combined with CAO algorithm to improve the best so- lution (path quality) obtained after each iteration of COA. The main purpose of using SA is to increase the exploitation by searching for the most promising regions identified by the CAO algorithm. The perfor- mance of the proposed CAOSA algorithm is evaluated on several scenarios under different settings consider- ing the fitness value, path cost, and execution time metrics. Simulation results showed superiority and ro- bustness of CAOSA algorithm compared to nine meta- heuristics such as Simulated Annealing (SA), Particle Swarm Optimization (PSO), Bat Algorithm (BA), Fire- fly optimization (FA), Grey Wolf Optimizer (GWO), Sine Cosine Algorithm (SCA), Whale Optimization Al- gorithm (WOA), Dragonfly Algorithm (DA), and the original Aquila Optimization (AO). It is also revealed that CAOSA can offer an optimized path that improves UAV path planning requirements significantly in com- plex environments
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    Enhancement of vehicular visible light communication using spherical detector and custom lens combinations
    (IEEE, 2023) Yahia, Selma; Meraihi, Yassine; Amar, Ramdane-Cherif; Tu Dac, Ho; Eldeeb, Hossien B.
    Vehicular Visible light communication (VLC) technology has recently attracted much interest from researchers and scientists. This technology enables connectivity between vehicles and infrastructures along the road by using vehicles’ headlights and taillights as wireless transmitters. The reliability of vehicle-to-vehicle (V2V) VLC systems is affected by several factors, such as car mobility, optics system design, and visibility conditions, where the first two have the most impact on the VLC system performance. This paper, therefore, focuses on the relative positions of the cars and the design of the optics, especially on the receiving end, which has been proposed with the use of a polar detector instead of the rectangular detectors commonly used in the literature. We investigate the achievable gain compared to the conventional detector for different vehicle locations, utilizing a professional optical system design and ray tracing approach. Then, to improve the performance, we introduce the utilization of an imaging receiver by integrating the polar detector with different optical commercial lens combinations, such as Fresnel and Aspherical lenses. To further improve the V2V system performance, we propose a novel optical lens combination design by integrating double-convex lens with half-Plano-concave lens, which allows the correction of more optical aberrations, such as chromatic and spherical aberration. Utilizing the non-sequential ray tracing tools, we designed these VLC systems and perform a realistic channel modeling study considering the typical 3D CAD models of vehicles and roads as well as the possibility of horizontal and vertical movement between the vehicles. Based on the channel impulse responses (CIRs) obtained from the ray tracing simulations, we analyzed the performance of V2V VLC systems with all lens combinations at different vehicle positions on the road. We further investigated the impact of different system parameters on the overall V2V system pe...
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    Machine learning-based research for COVID-19 detection, diagnosis, and prediction : a survey
    (Springer, 2022) Meraihi, Yassine; Gabis, Asma Benmessaoud; Mirjalili, Seyedali; Ramdane-Cherif, Amar; Alsaadi, Fawaz E
    The year 2020 experienced an unprecedented pandemic called COVID-19, which impacted the whole world. The absence of treatment has motivated research in all fields to deal with it. In Computer Science, contributions mainly include the development of methods for the diagnosis, detection, and prediction of COVID-19 cases. Data science and Machine Learning (ML) are the most widely used techniques in this area. This paper presents an overview of more than 160 ML-based approaches developed to combat COVID-19. They come from various sources like Elsevier, Springer, ArXiv, MedRxiv, and IEEE Xplore. They are analyzed and classified into two categories: Supervised Learning-based approaches and Deep Learning-based ones. In each category, the employed ML algorithm is specified and a number of used parameters is given. The parameters set for each of the algorithms are gathered in different tables. They include the type of the addressed problem (detection, diagnosis, or detection), the type of the analyzed data (Text data, X-ray images, CT images, Time series, Clinical data,..) and the evaluated metrics (accuracy, precision, sensitivity, specificity, F1-Score, and AUC). The study discusses the collected information and provides a number of statistics drawing a picture about the state of the art. Results show that Deep Learning is used in 79% of cases where 65% of them are based on the Convolutional Neural Network (CNN) and 17% use Specialized CNN. On his side, supervised learning is found in only 16% of the reviewed approaches and only Random Forest, Support Vector Machine (SVM) and Regression algorithms are employed
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    Nodes placement in wireless mesh networks using optimization approaches : a survey
    (Springer, 2022) Mekhmoukh Taleb, Sylia; Meraihi, Yassine; Benmessaoud Gabis, Asma; Mirjalili, Seyedali; Ramdane-Cherif, Amar
    Wireless mesh networks (WMNs) have grown substantially and instigated numerous deployments during the previous decade thanks to their simple implementation, easy network maintenance, and reliable service coverage. Despite these proprieties, the nodes placement of such networks presents many challenges for network operators. In this paper, we present a survey of optimization approaches implemented to address the WMNs nodes placement problem. These approaches are classified into four main categories: exact approaches, heuristic approaches, meta-heuristic approaches, and hybrid approaches. For each category, a critical analysis is drawn according to targeted objectives, considered constraints, type of positioned nodes (Mesh Router and Mesh Gateway), location (discrete or continuous), and environment (static or dynamic). In the end, several new key search areas for WMNs nodes placement are suggested
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    Double-gate MOSFET model implemented in verilog-AMS language for the transient simulation and the configuration of ultra low-power analog circuits
    (Polska Akademia Nauk, 2021) Smaani, Billel; Meraihi, Yassine; Nafa, Fares; Benlatreche, Mohamed Salah; Akroum, Hamza; Latreche, Saida
    This paper deals with the implementation of a DC and AC double-gate MOSFET compact model in the Verilog-AMS language for the transient simulation and the configuration of ultra low-power analog circuits. The Verilog-AMS description of the proposed model is inserted in SMASH circuit simulator for the transient simulation and the configuration of the Colpitts oscillator, the common-source amplifier, and the inverter. The proposed model has the advantages of being simple and compact. It was validated using TCAD simulation results of the same transistor realized with Silvaco Software
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    Grasshopper Optimization Algorithm: Theory, Variants, and Applications
    (IEEE, 2021) Meraihi, Yassine; Benmessaoud Gabis, Asma; Seyedali, Mirjalili; Amar Ramdane, Cherif
    Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired by the foraging and swarming behavior of grasshoppers in nature. The GOA algorithm has been successfully applied to solve various optimization problems in several domains and demonstrated its merits in the literature. This paper proposes a comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others. It provides the GOA variants, including multi-objective and hybrid variants. It also discusses the main applications of GOA in various fields such as scheduling, economic dispatch, feature selection, load frequency control, distributed generation, wind energy system, and other engineering problems. Finally, the paper provides some possible future research directions in this area.
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    Performance evaluation of a 60-GHz RoF-OFDM system for wireless applications
    (Springer, 2021) Yahia, Selma; Graini, Leila; Beddiaf, Safia; Benmessaoud Gabis, Asma; Meraihi, Yassine
    Radio over fiber (RoF) is an emerging and promising communication technology based on combining wireless and fiber-optic communications, where light is modulated with radio frequency signals and transmitted over the optical fiber. This paper proposes a modified RoF communication system based on the incorporation of the orthogonal frequency division multiplexing (OFDM) technique into RoF system, called RoF-OFDM. We focus on the transmission of OFDM signals at the frequency of 60 GHz. The performance of the proposed RoF-OFDM system is evaluated in terms of bit error rate (BER) and the constellation diagrams. For this purpose, we use three different formats of quadrature amplitude modulation (QAM) such as 16-QAM, 64-QAM, and 256-QAM, and various values of data rate, Optical Signal-to-Noise Ratio (OSNR), input optical power, and fiber length. Simulation results show that RoF-OFDM system using 16-QAM gives good results in terms of fiber length and OSNR. However, the best performance using 64-QAM is obtained in the case of optical power. In addition, in terms of bit rate, 16-QAM outperforms both 64-QAM and 256-QAM formats for a bit rate lower than 17 Gbit/s. Otherwise, the best performance is given with 64-QAM
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    A comprehensive survey of sine cosine algorithm : variants and applications
    (Springer, 2021) Benmessaoud Gabis, Asma; Meraihi, Yassine; Mirjalili, Seyedali; Ramdane‑Cherif, Amar
    Sine Cosine Algorithm (SCA) is a recent meta-heuristic algorithm inspired by the proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in 2016, SCA has attracted great attention from researchers and has been widely used to solve different optimization problems in several fields. This attention is due to its reasonable execution time, good convergence acceleration rate, and high efficiency compared to several well-regarded optimization algorithms available in the literature. This paper presents a brief overview of the basic SCA and its variants divided into modified, multi-objective, and hybridized versions. Furthermore, the applications of SCA in several domains such as classification, image processing, robot path planning, scheduling, radial distribution networks, and other engineering problems are described. Finally, the paper recommended some potential future research directions for SCA