Communications Internationales

Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/11

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Subject: search.filters.subject.Optimization

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Now showing 1 - 10 of 18
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    Data Caching in Edge Computing: A Survey
    (Institute of Electrical and Electronics Engineers Inc., 2024) Kara, Meliha Çağla; Benlakehal, Mohamed Elamine; Shayea, Ibraheem; Tussupov, Akhmet; Rzayeva, Leila
    As the Internet of Things (IoT) generates ever-increasing data streams, traditional cloud-centric architectures face crippling challenges in network latency, bandwidth consumption, and resource constraints. This paper explores how data caching in edge computing environments emerges as a potent solution, significantly impacting latency reduction, network efficiency, and overall system performance. We comprehensively review the landscape of edge IoT and data caching, analyze caching benefits and complexities, and delve into architectural integration, caching strategies, and algorithms tailored to address specific IoT challenges. Through case studies in chosen application domains, we quantify the performance improvements enabled by effective caching and pave the way for future research exploring novel caching methodologies and optimization techniques in the dynamic world of edge IoT.
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    Wireless Power Transfer Optimization Using Meta-heuristic Algorithms
    (IEEE, 2024) Bennia, Fatima; Boudouda, Aimad; Nafa, Fares
    The importance of Wireless Power Transfer (WPT) technology in biomedical implants to mitigate the risk of regeneration has increased significantly in recent years. WPT systems are dependent on key parameters such as the coupling coefficient (K), quality factor (Q), and mutual inductance (M), which play a crucial role in determining power transfer efficiency. These parameters are closely related to the geometric characteristics of the coils involved. Therefore, this study explores various meta-heuristic algorithms to search for optimal parameters that maximize power transfer efficiency. The initial results demonstrate that these algorithms perform well across different iterations. To confirm these findings, the study conducted comprehensive validation using Ansys Maxwell software to verify the optimal values obtained through optimization.
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    Wind Turbine Mechanical Speed Regulation Reliability Of Artificial Intelligent PSO-FLC Control
    (Institute of Electrical and Electronics Engineers Inc, 2024) Arabi, Marwa; Zennir, Youcef; Bourourou, Fares
    this paper addresses modeling and control of a wind energy conversion system (WECS). The WECS based on Permanent Magnet Synchronous Generator, PMSG. Wind energy transformed to mechanical energy via blade and turbine to give speed and torque to the PMSG. This mechanical speed will be controlled firstly with a classical MPPT-PI then will be optimized by a PSO algorithm, after that a new intelligent controller MPPT-FLC will be applied to show the efficiency of that's kind of controller on our WECS mechanical speed control. The analysis and discussion of the simulation results aim to enhance the reliability and efficiency of each suggested approach. Keywords - Wind turbine, Speed control, Optimization, FLC, PSO, PI.
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    Manta ray foraging optimization algorithm for solving the LEDs placement problem in indoor VLC systems
    (IEEE, 2022) Yahia, Selma; Meraihi, Yassine; Sadeki, Nesrine; Tellache, Mohamed; Mekhmoukh Taleb, Sylia; Refas, Souad; Benmessaoud Gabis, Asma
    Visible light communication is an excellent alternative to traditional Radio Frequency (RF) technology where many problems have been detected including saturation of the RF spectrum, making wireless communication unable to support the high demand of wireless connections. VLC allows communication between users using Light Emitting Diodes (LEDs) as transmitters and Photo-detectors (PDs) as receivers. The deployment of LEDs in indoor VLC Systems is an important issue that affects the coverage of the network. In this paper, we applied the Manta Rays Foraging Optimization (MRFO) algorithm for tackling the LEDs placement problem in indoor VLC systems. We formulate an optimization problem with the goal of maximizing coverage, throughput while ensuring the network requirements. The performance of MRFO was validated in terms of user coverage and throughput compared to Whale Optimization Algorithm (WOA), Bat Algorithm (BAT), and Particle Swarm Optimization (PSO). The simulation results demonstrated that MRFO is more effective than WOA, BAT, and PSO in determining optimal placement of LEDs
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    Optimal placement of DGs in the distribution networks using an analytical approach
    (IEEE, 2022) Dekhandji, Fatma Zohra; Baali, Habiba; Recioui, Abdelmadjid
    The work deals with the penetration of Distributed Generators (DGs) units into a simple radial system. An analytical optimization method is used to determine the optimal locations and sizes of the DGs minimizing the power distribution loss. A load flow method called Backward/Forward is used. In addition, a method based on the calculation of Voltage Stability Index (VSI) is employed to ensure the stability of the system after the placement of DG units
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    Document clustering analysis based on hybrid cuckoo search and K-means algorithm
    (IEEE, 2021) Boushaki, Saida Ishak; Bendjeghaba, Omar; Brakta, Noureddine
    The clustering is an interesting technique for unsupervised document organization in the World Wide Web (WWW). The most widely used partitioning clustering algorithm is K-means. However, it has an issue with random initialization, which might lead to local optimum situations. In fact, metaheuristics-based clustering has demonstrated their efficiency to reach a global solution instead of local one. The Cuckoo search (CS) has been widely used for the clustering problem. However, the number of iterations grows dramatically when the dataset is high dimensional like the documents. In this study, the hybridization cuckoo search and K-means algorithms for the document clustering are analyzed. So, three hybrid algorithms are investigated and compared. The performance and the efficiency of the proposed algorithms are evaluated using Reuters 21578 Text Categorization Benchmark Dataset. The obtained results show the capability of the new approaches to generate more compact clustering and enhancing purity and F-measure clustering qualities
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    Accelerated modified sine cosine algorithm for data clustering
    (IEEE, 2021) Boushaki, Saida Ishak; Bendjeghaba, Omar; Brakta, Noureddine
    In artificial intelligence, data mining is a process that automatically discover valuable information from huge amounts of data in order to obtain knowledge. The most important unsupervised technique of data mining is the clustering technic, which his main task is dividing the dataset into homogeneous groups. Metaheuristics based clustering is an actual research area where optimization algorithms have demonstrated their efficiencies to provide near optimal solutions to this problem in a reasonable time, including the recent Sine Cosine metaheuristic Algorithm (SCA). However, its convergence rate is still rather slow. In this paper, an upgraded adaptation of SCA is proposed to improve the exhibition capacities of the quest strategy for ideal results for data Clustering problem, named AMSCAC. In this algorithm, both the local and global search procedures are enhanced by additional strategy. The experimental results on five standard datasets are promising and confirm the superiority of AMSCAC, for the clustering results over SCA, cuckoo search algorithm (CS), differential evolution algorithm (DE), and genetic algorithm (GA)
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    Entropy generation optimization of a hemispherical anchor agitated batch reactor
    (American Institute of Physics, 2019) Baghli, Houda; Tchouar, Noureddine; Merah, Abdelkrim
    The entropy generation optimization of a hemispherical anchor agitated batch reactor has been studied, to optimize the heat transfer in the process of production of a cosmetic cream cooled by a jacket at industrial scale. The main objective of this optimization of the cooling condition was the improvement of the product quality and the reduction the energy consumption of the process. The phenomenon considered is two-dimensional, axisymmetric and permanent. The entropy generation optimization has been carried out successfully by the simulation of the heat transfer throw the reactor wall and the agitated fluid. The results give the optimum speed velocity for agitation and the optimal cooling time and coolant temperature
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    PMU reporting rate optimization for data transfer enhancement in wide area monitoring systems
    (IEEE, 2020) Afaf, Saoud; Recioui, Abdelmadjid
    The main factor to enabling a smart grid system is the perfect link between the existing grid systems and informationcommunication technologies (ICTs). As data become larger, latency and reliability requirements for different smart grid applications vary widely and are not easily obtainable to practitioners. In this work, data transfer enhancement in wide area monitoring (WAMS) applications is addressed. The improvement is done using optimization of PMU reporting rate which is fixed in the standardized WAMS operation. The reporting rate is considered as a variable parameter that needs to be optimized for the enhancement of the sytem performance. The results reveal that this factor affects the operation of the WAMS and can be exploited to improve the overall system performance. The standards must take into account the variable nature of this parameter and should make it tunable by the users
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    Optimization of the compression systems using genetic algorithm
    (IEEE, 2016) Zammoum Boushaki, Razika; Kessal, Farida; Bentarzi, Hamid