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Reliability-aware swarm based multi-objective optimization for controller placement in distributed SDN architecture

Digital Communications and Networks 2024年第5期10卷 1245-1257页

作者： Abeer A.Z.Ibrahim Fazirulhisyam Hashim Aduwati Sali Nor K.Noordin Keivan Navaie Saber M.E.Fadul Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia Wireless and Photonics Networks Research Centre(WiPNET) Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia Department of Communication and Computer Engineering College of Engineering and Medical SciencesKhartoum11111Sudan School of Computing and Communications Lancaster UniversityLancasterLA14YWUnited Kingdom Department of Electrical and Electronics Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia

The deployment of distributed multi-controllers for Software-Defined Networking(SDN)architecture is an emerging solution to improve network scalability and ***,the network control failure affects the dynamic resource allocation in distributed networks resulting in network disruption and low ***,we consider the control plane fault tolerance for cost-effective and accurate controller location models during control plane *** fault-tolerance strategy has been applied to distributed SDN control architecture,which allows each switch to migrate to next controller to enhance network *** this paper,the Reliable and Dynamic Mapping-based controller Placement(RDMCP)problem in distributed architecture is framed as an optimization problem to improve the system reliability,quality,and *** considering the bound constraints,a heuristic state-of-the-art controller Placement Problem(CPP)algorithm is used to address the optimal assignment and reassignment of switches to nearby controllers other than their regular *** algorithm identifies the optimal controller location,minimum number of controllers,and the expected assignment costs after failure at the lowest effective cost.A metaheuristic Particle Swarm Optimization(PSO)algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and *** effectiveness of our hybrid RDMCP-PSO was then evaluated using extensive experiments and compared with other baseline *** findings demonstrate that the proposed hybrid technique significantly increases the network performance regarding the controller number and load balancing of the standalone heuristic CPP algorithm.

关键词： Software defined networking Dynamic mapping Particle swarm optimization Reliability Multi-objective optimization Evolutionary

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Parameters Estimation of Modified Triple Diode Model of PSCs Considering Charge Accumulations and Electric Field Effects Using Puma Optimizer

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computer Modeling in engineering & Sciences 2025年第4期143卷 723-745页

作者： Amlak Abaza Ragab A.El-Sehiemy Mona Gafar Ahmed Bayoumi Electrical Engineering Department Faculty of EngineeringKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Computer Engineering and Information College of Engineering inWadi AlddawasirPrince Sattam Bin Abdulaziz UniversityKharj16278Saudi Arabia Machine Learning and Information Retrieval Department Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Electrical Department Faculty of Engineering and TechnologyBadr University in CairoBadr11829Egypt Physics and Mathematics Department Faculty of EngineeringKafrelsheikh UniversityKafrelsheikh33516Egypt College of Engineering Al-Ayen UniversityThi-Qar64001Iraq

Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution *** study measures the effectiveness of the Puma optimizer(PO)algorithm in parameter estimation of PSC(perovskite solar cells)dynamic models with hysteresis consideration considering the electric field effects on *** models used in this study will incorporate hysteresis effects to capture the time-dependent behavior of PSCs *** PO optimizes the proposed modified triple diode model(TDM)with a variable voltage capacitor and resistances(VVCARs)considering the hysteresis *** suggested PO algorithm contrasts with other wellknown optimizers from the literature to demonstrate its *** results emphasize that the PO realizes a lower RMSE(Root mean square errors),which proves its capability and efficacy in parameter extraction for the *** statistical results emphasize the efficiency and supremacy of the proposed PO compared to the other well-known competing *** convergence rates show good,fast,and stable convergence rates with lower RMSE via PO compared to the other five competitive ***,the lowermean realized via the PO optimizer is illustrated by the box plot for all optimizers.

关键词： Dynamic model of PSCs puma optimizer parameter estimation triple diode model

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EXPLORING INFLUENTIAL FACTORS IN KNOWLEDGE SHARING WITHIN INDONESIAN PRISONS 22

EXPLORING INFLUENTIAL FACTORS IN KNOWLEDGE SHARING WITHIN IN...

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22nd International Conference on e-Society 2024, ES 2024 and 20th International Conference on Mobile Learning 2024, ML 2024

作者： Imandeka, Ejo Hidayanto, Achmad Nizar Suhartanto, Heru Pidanic, Jan Department of Computer Science Faculty of Computer Science University of Indonesia Depok Indonesia Department of Electrical Engineering Faculty of Electrical Engineering and Informatics Pardubice University Pardubice Czech Republic

The exchange of knowledge is widely recognized as a crucial aspect of effective knowledge management. When it comes to sharing knowledge within Prison settings, things get complicated due to various challenges such as limited resources, social stigma, isolation, communication barriers, and security concerns. Additionally, there's a scarcity of resources dedicated to promoting knowledge sharing in secure environments. This study aims to dig deep into the key factors that influence how knowledge is shared in Indonesian prisons. To navigate this intricate terrain, the study uses questionnaires distributed among Prison officers to understand the complex relationship between the identified critical factors and knowledge sharing in Prison. Leadership support, organizational culture, organizational structure, incentives, and individual beliefs emerge as pivotal elements in knowledge sharing. It's also noted that the connection between these critical factors and the intention to share knowledge is significantly influenced by organizational structure. Recognizing and addressing critical factors in knowledge sharing within prisons not only improves rehabilitation within prison walls but also transforms the broader criminal justice system. This approach fosters evidence-based practices, better communication, and a comprehensive understanding of factors leading to successful rehabilitation and reduced recidivism, ultimately creating a more just and effective system. © 2024 International Conferences e-Society 2024 and Mobile Learning 2024. All rights reserved.

关键词： Critical Factors Indonesia Knowledge Knowledge Sharing Prison

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Performance *** Comparative Analysis of Multimodal Bilinear Pooling Fusion Approaches for Deep Learning-Based Visual Arabic-Question Answering Systems

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computer Modeling in engineering & Sciences 2025年第4期143卷 373-411页

作者： Sarah M.Kamel Mai A.Fadel Lamiaa Elrefaei Shimaa I.Hassan Electrical Engineering Department Faculty of Engineering at ShoubraBenha UniversityCairo11629Egypt Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer and Systems Engineering Faculty of Engineering and TechnologyBadr University in Cairo(BUC)Cairo11829Egypt Communication Systems Engineering Department Faculty of EngineeringBenha National UniversityObour11846QalyubiaEgypt

Visual question answering(VQA)is a multimodal task,involving a deep understanding of the image scene and the question’s meaning and capturing the relevant correlations between both modalities to infer the appropriate *** this paper,we propose a VQA system intended to answer yes/no questions about real-world images,in *** support a robust VQA system,we work in two directions:(1)Using deep neural networks to semantically represent the given image and question in a fine-grainedmanner,namely ResNet-152 and Gated Recurrent Units(GRU).(2)Studying the role of the utilizedmultimodal bilinear pooling fusion technique in the *** the model complexity and the overall model *** fusion techniques could significantly increase the model complexity,which seriously limits their applicability for VQA *** far,there is no evidence of how efficient these multimodal bilinear pooling fusion techniques are for VQA systems dedicated to yes/no ***,a comparative analysis is conducted between eight bilinear pooling fusion techniques,in terms of their ability to reduce themodel complexity and improve themodel performance in this case of VQA *** indicate that these multimodal bilinear pooling fusion techniques have improved the VQA model’s performance,until reaching the best performance of 89.25%.Further,experiments have proven that the number of answers in the developed VQA system is a critical factor that *** the effectiveness of these multimodal bilinear pooling techniques in achieving their main objective of reducing the model *** Multimodal Local Perception Bilinear Pooling(MLPB)technique has shown the best balance between the model complexity and its performance,for VQA systems designed to answer yes/no questions.

关键词： Arabic-VQA deep learning-based VQA deep multimodal information fusion multimodal representation learning VQA of yes/no questions VQA model complexity VQA model performance performance-complexity trade-off

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A learning-based approach to fault detection and fault-tolerant control of permanent magnet DC motors

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Journal of engineering and Applied Science 2023年第1期70卷 109页

作者： Sardashti, Abolghasem Nazari, Jamal Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Faculty of Electrical Biomedical and Mechatronics Engineering Qazvin Branch Islamic Azad University Qazvin Iran

In the context of Industry 4.0, which prioritizes intelligent and efficient solutions for industrial systems, this paper introduces an innovative methodology for fault detection and fault-tolerant control of DC motors. Leveraging the capabilities of machine learning and reinforcement learning, our approach aims to achieve optimal performance while maintaining a low computational burden. At the heart of our strategy lies a reinforcement learning-enhanced proportional-integral controller meticulously designed for precise positioning of DC motors. Through extensive comparative analysis, we establish the superiority of this controller in terms of precision, efficiency, and user accessibility when compared to traditional techniques. To ensure robust fault detection, we synergize a model-based observer with Mahalanobis distance-based outlier analysis, creating a swift and accurate diagnostic method for sensor faults. In cases of sensor malfunctions, an internal model-based control strategy comes into play, enabling the system to uphold its effectiveness despite disruptions. The effectiveness of our proposed methods is vividly demonstrated through simulations in the MATLAB environment, utilizing a DC motor subjected to sensor failures. The results unequivocally highlight the advantages of our approach, showcasing improved precision, faster operation, cost-effectiveness, and streamlined simplicity. As such, our approach finds suitability for industrial applications. In our quest to strike a delicate balance between performance and complexity, our techniques are purposefully crafted to provide intelligent yet pragmatic solutions that promote reliability, safety, and sustainability. This paper contributes to the evolving landscape of intelligent industrial solutions by offering a comprehensive framework that optimizes performance while minimizing complexity and costs. In doing so, we lay the foundation for a more efficient and resilient industrial ecosystem. © 2023, faculty o

关键词： Fault detection

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Distribution Management Systems for Smart Grid:Architecture,Work Flows,and Interoperability

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 300-308页

作者： Rabih A.Jabr Izudin Dzafic the Department of Electrical and Computer Engineering American University of BeirutBeirut 11072020Lebanon the Faculty of Electrical Engineering University of SarajevoSarajevo 71000Bosnia and Herzegovina

The smart grid integrates advanced sensors,a two-way communication infrastructure,and high-performance computation-based *** distribution management systems for smart grid include several functions for manipulating legacy voltage control devices and distributed energy resources through closed-loop volt/var control,leading to wide-area regulation of voltages in the presence of fluctuating *** other primary distribution network analysis application is concerned with automatic fault location and service restoration following fault events,aiming to provide the grid with autonomous intelligence for *** technologies are vital to enable the computing applications of distribution networks,whether they work in centralized or distributed *** paper presents the state of the art in distribution management system architectures and modern workflows showing data exchange,practical parallel implementations designed to handle large amounts of data,in addition to communication standards that serve as interoperability *** demystifies the relationship between different functions developed independently by power system researchers and shows their operation as a complete system,thus placing them in a better context for future research and development.

关键词： Cyber security data communication power distribution networks self-healing software architecture voltage control.

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Review of sub-synchronous interaction in wind integrated power systems: classification, challenges, and mitigation techniques

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Protection and control of Modern Power Systems 2023年第2期8卷 13-38页

作者： Neevatika Verma Narendra Kumar Saket Gupta Hasmat Malik Fausto Pedro García Márquez Department of Electrical Engineering Delhi Technological UniversityDelhi 110042India Department of Electrical Power Engineering Faculty of Electrical EngineeringUniversiti Teknologi Malaysia(UTM)81310 JohorMalaysia Ingenium Research Group DepartmentUniversidad Castilla-La Mancha13071 Ciudad RealSpain Department of Electrical Engineering Graphic Era Deemed to be UniversityDehradun 248002India Instrumentation and Control Engineering Department Bharati Vidyapeeth’s College of EngineeringNew Delhi 110056India

Emerging sub-synchronous interactions(SSI)in wind-integrated power systems have added intense attention after numerous incidents in the US and China due to the involvement of series compensated transmission lines and power electronics *** phenomenon occurs when two power system elements exchange energy below the synchro-nous *** phenomenon related to wind power plants is one of the most significant challenges to main-taining stability,while SSI phenomenon in practical wind farms,which has been observed recently,has not yet been described on the source of conventional SSI *** paper first explains the traditional development of SSI and its classification as given by the IEEE,and then it proposes a classification of SSI according to the current research status,reviews several mitigation techniques and challenges,and discusses analysis techniques for *** paper also describes the effect of the active damping controllers,control scheme parameters,degree of series compensation,and various techniques used in wind power plants(WPPs).In particular,a supplementary damping controller with converter controllers in Doubly Fed Induction Generator based WPPs is briefly *** paper provides a real-istic viewpoint and a potential outlook for the readers to properly deal with SSI and its mitigation techniques,which can help power engineers for the planning,economical operation,and future expansion of sustainable development.

关键词： Damping controller Doubly fed induction generator(DFIG) Series compensations Sub-synchronous interactions(SSI) Sub-synchronous resonance(SSR)

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Optimal MBU Positioning under Fault Scenario for Distribution Networks with high PV Penetration 14

Optimal MBU Positioning under Fault Scenario for Distributio...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Caruana, Cedric Bhattacharya, Somesh Raute, Reiko Micallef, Alexander Scerri, Kenneth Department of Electrical Engineering Faculty of Engineering University of Malta Msida Malta Department of Systems and Control Faculty of Engineering University of Malta Malta

ISBN: (纸本)9781837242689

Faults on distribution networks due to abnormal weather events can lead to disruption and can cause high socio-economic losses. In line with the rising frequency of such events, the paper proposes an algorithm for the optimal deployment of mobile battery units to restore sections of the network. The considered battery units are rated at 1MVA to keep them realistic for the mobile application. The placement algorithm is formulated as a mixed integer mathematical optimisation problem. Sectionalising/tie switches are assumed on each branch of the network in order to increase the restoration configuration flexibility. Photovoltaic systems, distributed along the network, are allowed to contribute to the restored network sections. A number of critical loads are defined and these are prioritised in the restoration process. The objective function also considers the reduction of the overall renewable energy curtailment. The performance of the algorithm is tested on the IEEE 33 bus network with four tie lines. Scenarios with increasing levels of PV power are considered and the effect of incorporating the PV power is studied. © The Institution of engineering & Technology 2024.

关键词： Mixed-integer linear programming

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Intelligent Predetermination of Generator Tripping Scheme: Knowledge Fusion-based Deep Reinforcement Learning Framework

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 66-75页

作者： Lingkang Zeng Wei Yao Ze Hu Hang Shuai Zhouping Li Jinyu Wen Shijie Cheng State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronics EngineeringHuazhong University of Science and TechnologyWuhan 430074China Dispatching and Control Center Central China Branch of State Grid Corporation of ChinaWuhan 430077China. Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN 37996USA

Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power *** improve efficiency of predetermination,this paper proposes a framework of knowledge fusion-based deep reinforcement learning(KF-DRL)for intelligent predetermination of ***,the Markov Decision Process(MDP)for GTS problem is formulated based on transient instability ***,linear action space is developed to reduce dimensionality of action space for multiple controllable ***,KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making *** can enhance the efficiency and learning ***,the graph convolutional network(GCN)is introduced to the policy network for enhanced learning *** simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.

关键词： Deep reinforcement learning generator tripping scheme graph convolutional network invalid action masking knowledgefusion

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Implementation of 5G Network Slicing Using Open Source Software 12

Implementation of 5G Network Slicing Using Open Source Softw...

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12th International electrical engineering Congress, iEECON 2024

作者： Vanichchanunt, Pisit Ritruechai, Onpimon Wuttiananchai, Navy Thossaporn, Peeraporn Wuttisittikulkij, Lunchakorn Paripurana, Sukritta King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand Chulalongkorn University Faculty Of Engineering Department Of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9798350383591

In modern communications, network slicing is essen-tial network operation for creating and managing an independent logical network which meets the requirement of a service. Net-work slicing enables available network resources to be managed and allocated efficiently and dynamically according to varying demands of users. This paper aims to design and implement 5G network slicing using open source software in order to serve very low latency services. The implementation requires the integration of orchestration, network function virtualization, and software defined network technologies to deploy necessary network functions and to manage the life cycles of network slices. Open source software tools such as Open5GS, Open Source MANO, OpenStack, OpenDaylight, and srsRAN are selected for implementing 5G core, orchestration and management functions, cloud computing platform, software defined network, and radio access network respectively since they offer compatibility in the software integration as well as allow the prototype to be created in a timely and economical manner. To obtain very low latency, User Plane Function and edge computing are implemented based on the latency of internal connections. In the experiment, different scenarios of network slices are deployed and tested to measure the key performance indices such as a delay, download speed and upload speed. The results show that the implemented network slices can offer very low latency at the expense of available bandwidth reduction due to the communication for orchestration and management in the hardware. However, this can be improved by using hardware with higher performance. © 2024 IEEE.

关键词： Network function virtualization

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