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Articles 1621 - 1650 of 13035

Full-Text Articles in Computer Engineering

Development Opportunities And Application Prospects Of Aero-Engine Simulation Technology Under Digital Transformation, Jianguo Cao Jan 2023

Development Opportunities And Application Prospects Of Aero-Engine Simulation Technology Under Digital Transformation, Jianguo Cao

Journal of System Simulation

Abstract: The development of China's social economy and the improvement of its national defense capability in the new era put forward higher requirements for the development of aero-engines. It is urgent to promote the digital transformation of aero-engines in order to achieve coordinated, agile and efficient aero-engine development. Based on the current research and development of aero-engine in China, this paper clarifies the new connotation of "speediness and efficiency, accurate mapping, comprehensive coverage, and dynamic prediction" given by the development of emerging cutting-edge technologies to aero-engine simulation technology, as well as the new technical features of "spatio-temporal ubiquity, data driven, …

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Chameleon Swarm Algorithm For Segmental Variation Learning Of Population And S-Type Weight, Damin Zhang, Yi Wang, Linna Zhang Jan 2023

Chameleon Swarm Algorithm For Segmental Variation Learning Of Population And S-Type Weight, Damin Zhang, Yi Wang, Linna Zhang

Journal of System Simulation

Abstract: It is the best choice for intelligent algorithms to be applied to specific fields to explore strong searching ability, good reliability and stability.In this paper, aiming at the defects of chameleon swarm algorithm, such as unstable solution, low convergence accuracy and unbalanced search and development, a chameleon swarm algorithm (RMSCSA) based on population diversity segmental mutation learning and S-type weight is proposed. The refraction mirror learning strategy (RML) is introduced to make the chameleon more consistent with the observation in nature and enhance its diversity. The introduction of segmental variation of population diversity can keep the individuals with poor …

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Research On Vr Experience Comfort Based On Motion Perception, Wei Quan, Chao Wang, Xuena Geng, Cheng Han Jan 2023

Research On Vr Experience Comfort Based On Motion Perception, Wei Quan, Chao Wang, Xuena Geng, Cheng Han

Journal of System Simulation

Abstract: A VR video comfort evaluation model based on motion perception is proposed for viewers who will feel discomfort such as vertigo and nausea after a virtual reality (VR) experience. By performing dense optical flow estimation on stereoscopic VR video and calculating the video frame velocity matrix by analyzing the horizontal and vertical motions in the scene, the frame acceleration feature extraction methods based on frame difference method and based on time domain are proposed. Taking the extracted velocity, acceleration and other motions features as input, a model is established using the support vector regression algorithm, and VR video experience …

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Research On Intelligent Prediction Method Of Wargaming Air Mission, Dayong Zhang, Jingyu Yang, Xi Wu Jan 2023

Research On Intelligent Prediction Method Of Wargaming Air Mission, Dayong Zhang, Jingyu Yang, Xi Wu

Journal of System Simulation

Abstract: The efficient, accurate and automatic judgment of the combat mission or intention of the enemy's air targets in the battlefield is the basis of situation awareness and the key to the allocation of auxiliary combat resources. Combined with the calculation characteristics of feed forward deep neural network and long-term and short-term memory network model, two targeted basic index learners are designed, and then the weighted combination is carried out according to the cross entropy of the basic index, which can be used to further train the evaluation index of the learner. It can not only effectively prevent the model …

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Research On Intelligent Optimization Method Of Combat Sos Based On Gabc Algorithm, Hucheng Zhang, Jingyu Yang Jan 2023

Research On Intelligent Optimization Method Of Combat Sos Based On Gabc Algorithm, Hucheng Zhang, Jingyu Yang

Journal of System Simulation

Abstract: In order to solve the problem that exploratory simulation can not traverse the solution space quickly, and provide the auxiliary decision-making scheme in real time, a genetic algorithm based on classifier is proposed. The framework of simulation optimization method based on the algorithm is established. It can find the optimal solution according to the dynamic changes of key factors and decision targets of the system, which is suitable for such as seeking the best efficiency-cost ratio scheme and the optimization of the optimal power deployment and other systems. Based on the simulation bed system of the National Defense …

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Large-Scale Multi-Objective Natural Computation Based On Dimensionality Reduction And Clustering, Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin Jan 2023

Large-Scale Multi-Objective Natural Computation Based On Dimensionality Reduction And Clustering, Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin

Journal of System Simulation

Abstract: In multi-objective optimization problems, as the number of decision variables increases, the optimization ability decreases significantly. To solve "dimension disaster", a large-scale multi-objective natural computation method based on dimensionality reduction and clustering is proposed. The decision variables are optimized by locally linear embedding(LLE) to obtain the representation of high-dimensional variables in the low-dimensional space, then the individuals are grouped through K-means to select the appropriate guide individuals for the population to strengthen the convergence and diversity. To verify the effectiveness, the method is applied to the multi-objective particle swarm optimization algorithm and the non-dominated sorting genetic algorithm. The convergence …

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Dynamic Risk Assessment Of Vocs Cross Regional Flow Based On Petri Nets, Guangqiu Huang, He Wang Jan 2023

Dynamic Risk Assessment Of Vocs Cross Regional Flow Based On Petri Nets, Guangqiu Huang, He Wang

Journal of System Simulation

Abstract: In order to evaluate the interaction between regions due to the cross regional flow of VOCs(volatile organic compounds) under polluted weather, a dynamic risk assessment method of cross regional flow of VOCs is proposed by using Petri net modeling method. The migration paths of VOCs between multiple potential pollution sources and contaminated areas are determined by HYSPLIT model, and the relationship between each migration path is described by Petri net; the dynamic risk assessment method is defined, and the calculation of dynamic risk is integrated into the operation of functional Petri net; through case analysis, the dynamic risk assessment …

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Simulation-Based Adaptive Dynamic Scheduling For Bi-Objective Parallel Multi-Processor Open Shop, Yarong Chen, Shuchen Guan, Chengjun Huang, Lixia Zhu, Fuhder Chou Jan 2023

Simulation-Based Adaptive Dynamic Scheduling For Bi-Objective Parallel Multi-Processor Open Shop, Yarong Chen, Shuchen Guan, Chengjun Huang, Lixia Zhu, Fuhder Chou

Journal of System Simulation

Abstract: Aiming at the parallel multi-processor open shop scheduling problem with uncertain job's release time,processing time and urgent jobs, an adaptive dynamic method integrating FlexSim simulation model and NSGA-Ⅱ algorithm is designed to optimize the bi-objectives of TWC(total weighted completion time) and TWT(total weighted tardiness). By using the FlexSim simulation model, this method determines the adaptive scheduling cycle according to the dynamic workload of the open shop, and conducts right-shift rescheduling to the urgent jobs. NSGA-Ⅱ algorithm is used to generate the bi-objective optimization scheduling scheme. Experimental results of a grain sorting shop show that compared with the rule-based real-time …

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Research On System Of Virtual-Reality Fusion And Inquiry-Based Learning, Yongning Zhu, Zeru Lou, Tianxiang Wu, Jianmin Wang Jan 2023

Research On System Of Virtual-Reality Fusion And Inquiry-Based Learning, Yongning Zhu, Zeru Lou, Tianxiang Wu, Jianmin Wang

Journal of System Simulation

Abstract: With the increasing interest in personalized and self-motivated education, emphasizing active learning and practical experiences, inquiry-based learning (IBL) is attracting interest in education. Considering the requirement for inquiry-based education, a framework of full process inquiry-based learning environment in the real-virtual worlds is designed. As an example, a mixed-reality chemical experiment system is developed. The metadata including user behavior data, interactive suite status and interactive interface status is collected through physical sensing. By mapping real-world status to the virtual world avatar, virtual experiments are simulated with computational dynamic solvers and real-time rendering. The generated images are sent back to the …

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Knn Fault Detection Based On Reconstruction Error And Multi-Block Modeling Strategy, Jing Zheng, Weili Xiong, Xiaodong Wu Jan 2023

Knn Fault Detection Based On Reconstruction Error And Multi-Block Modeling Strategy, Jing Zheng, Weili Xiong, Xiaodong Wu

Journal of System Simulation

Abstract: For the fault monitoring algorithm based on k-nearest neighbor (kNN), the abnormal information that caused the fault is easy to be overwhelmed by the normal operating condition information, which leads to the problem of untimely fault detection and low alarm rate. A kNN fault monitoring method based on reconstruction error is proposed using auto-encoder and multi-block modeling strategy. The method uses the normal working condition data set to train the auto-encoder model, and extracts the reconstruction error based on the model to solve the problem that abnormal information is easy to be overwhelmed. Further considering the fault characteristics such …

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Uniform Experimental Design With Constrained Region Based On Fruit Fly Algorithm, Jiawei Zhou, Xin Du, Youcong Ni, Hu Zhang, Hao Zhang, Haoran Ni, Feng Wang Jan 2023

Uniform Experimental Design With Constrained Region Based On Fruit Fly Algorithm, Jiawei Zhou, Xin Du, Youcong Ni, Hu Zhang, Hao Zhang, Haoran Ni, Feng Wang

Journal of System Simulation

Abstract: To solve the problems that existing two-phase differential evolutionary algorithms still have poor diversity of population distribution and weak local search ability in solving uniform designs in constrained experimental region, a new two-phase fruit fly optimization algorithm (ToPFOA) based on uniform experimental design is proposed. In the first stage, fruit fly search strategy combined with differential operator, K-means clustering and external document updating the centers of clusters is used todynamically improve distribution diversity of population in constrained region. In the second stage, a new fruit fly operator is designed to improve local search ability in constrained region. …

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Drosophila Retina Simulation System And The Emergence Of Orientation Selectivity, Ziyu Liu, Yiran Zhuo, Zhuoyi Song Jan 2023

Drosophila Retina Simulation System And The Emergence Of Orientation Selectivity, Ziyu Liu, Yiran Zhuo, Zhuoyi Song

Journal of System Simulation

Abstract: To investigate the biophysical mechanisms underlying the Drosophila retinal computations, a piece of simulation software is constructed. By constructing the connectivity of the optical structure of the Drosophila compound eye with the neural network and retinal neuronal information encoding processes,, the retinal transformation from the light to the electrical signals is simulated. The photo-transduction model is optimized by a stochastic process. The generating mechanism of orientation selectivity (OS) is explored in the Drosophila retina's output neurons through a simulation system. Experiments show that with comparable simulation accuracy, the simulation speed increases by 40 times. The software can now be …

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Research On Multiple Filter Signal Compensation For Washout Algorithm Optimization Of Flight Simulator, Weichao Liu, Hui Wang Jan 2023

Research On Multiple Filter Signal Compensation For Washout Algorithm Optimization Of Flight Simulator, Weichao Liu, Hui Wang

Journal of System Simulation

Abstract: Aiming at the defects of signal loss and poor adaptability of the classical washout algorithm when applied to flight simulator, an optimization scheme of washing algorithm based on multiple filtering signal compensation is proposed. Analyzing the lost signal in classical washout algorithm, intercepting the lost signals to the depth filter with depth filtering strategy, basing on human perception errors and platform movement margin, after multiple filtering signal to certain proportion respectively compensation to the three channel of washout algorithm to achieve the maximum reduction of signal loss, thus reducing human perception error. The classical washing algorithm and the improved …

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Modulation Recognition Method Of Mixed Signal Based On Intelligent Analysis Of Cyclic Spectrum Section, Yu Du, Xinquan Yang, Jianhua Zhang, Suchun Yuan, Huachao Xiao, Jingjing Yuan Jan 2023

Modulation Recognition Method Of Mixed Signal Based On Intelligent Analysis Of Cyclic Spectrum Section, Yu Du, Xinquan Yang, Jianhua Zhang, Suchun Yuan, Huachao Xiao, Jingjing Yuan

Journal of System Simulation

Abstract: Aiming at the problems of low intelligence and poor adaptability for the existing mixed signal recognition methods, an intelligent recognition method based on cyclic spectral cross section and deep learning is proposed. For common mixed communication signals, the characteristics of zero frequency cross section of cyclic spectrum are theoretically deduced and analyzed. Two new pre-processing methods, nonlinear segmental mapping and directional pseudo-clustering are proposed, which can effectively improve the adaptability and consistency of cross section features. The pre-processed feature graph is combined with the residual network (ResNet), and the deep learning network is used to mine and analyze the …

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Short-Time Human Activity Recognition Based On Wavelet Features Matching, Benyue Su, Li Zhang, Qingxuan He, Min Sheng Jan 2023

Short-Time Human Activity Recognition Based On Wavelet Features Matching, Benyue Su, Li Zhang, Qingxuan He, Min Sheng

Journal of System Simulation

Abstract: The selection of features is the key problem in the study of human activity recognition. In order to obtain sufficient and stable behavioral features, long-time behavioral data that exceed one behavior cycle are often processed, while short-time behavioral data with less than one behavioral cycle are usually unstable, making it difficult to achieve accurate and stable identification. This paper proposes a short-time human activity recognition method based on the combination of wavelet transform and template matching. Coefficient features are extracted using wavelet transform method. The features of the short-time test samples are matched with the features in the template …

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Scheduling Optimization Of Aluminum Extrusion Production Line Based On Timed Petri Net And Bso Algorithm, Yali Wu, Shuting He, Yanxi Yang, Lianqiang Feng, Fuqiang Wang, Yulu Chen Jan 2023

Scheduling Optimization Of Aluminum Extrusion Production Line Based On Timed Petri Net And Bso Algorithm, Yali Wu, Shuting He, Yanxi Yang, Lianqiang Feng, Fuqiang Wang, Yulu Chen

Journal of System Simulation

Abstract: For the problems of long production period and low efficiency caused by the complicated processes and large scheduling capacity of aluminum extrusion production line in industrial production, a timed Petri net (TdPN) scheduling model of aluminum extrusion production line is proposed and analyzed for reasonableness. The brain storm optimization (BSO) algorithm is introduced into the model, and an optimized scheduling algorithm for aluminum extrusion scheduling problems is proposed based on the individual encoding and decoding methods. The simulated annealing local search mechanism is used to improve the performance of BSO algorithm in the later stage, which can achieve the …

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A Multi-Resolution Simulation Modeling Method, Zhaopeng Liu, Xinhai Xu, Bowen Yuan, Jinlu Zhang Jan 2023

A Multi-Resolution Simulation Modeling Method, Zhaopeng Liu, Xinhai Xu, Bowen Yuan, Jinlu Zhang

Journal of System Simulation

Abstract: Aiming at the resolution gap between the operation task issued by the high-level commanders and the simulation system model instructions in the human-in-the-loop simulation deduction, a multi-resolution modeling method based on behavior tree is proposed. By improving the behavior tree syntax, the low-resolution combat missions are disaggregated into high-resolution simulation system instructions. By designing a decision model embedded in the behavior tree, the problem of resource uncertainty and execution effect uncertainty faced in the execution of model instructions is solved. A combat scenario for seizing air supremacy is designed to verify the effectiveness of the method.

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A Path Planning Framework For Multi-Agent Robotic Systems Based On Multivariate Skew-Normal Distributions, Peter Estephan Jan 2023

A Path Planning Framework For Multi-Agent Robotic Systems Based On Multivariate Skew-Normal Distributions, Peter Estephan

Theses, Dissertations and Capstones

This thesis presents a path planning framework for a very-large-scale robotic (VLSR) system in an known obstacle environment, where the time-varying distributions of agents are applied to represent the multi-agent robotic system (MARS). A novel family of the multivariate skew-normal (MVSN) distributions is proposed based on the Bernoulli random field (BRF) referred to as the Bernoulli-random-field based skew-normal (BRF-SN) distribution. The proposed distributions are applied to model the agents’ distributions in an obstacle-deployed environment, where the obstacle effect is represented by a skew function and separated from the no-obstacle agents’ distributions. First, the obstacle layout is represented by a Hilbert …

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Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh Jan 2023

Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh

Browse all Theses and Dissertations

The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …

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Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha Jan 2023

Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha

Browse all Theses and Dissertations

Smart cities have emerged to tackle many critical problems that can thwart the overwhelming urbanization process, such as traffic jams, environmental pollution, expensive health care, and increasing energy demand. This Master thesis proposes efficient and high-quality cloud-based machine-learning solutions for efficient and sustainable smart cities environment. Different supervised machine-learning models for air quality predication (AQP) in efficient and sustainable smart cities environment is developed. For that, ML-based techniques are implemented using cloud-based solutions. For example, regression and classification methods are implemented using distributed cloud computing to forecast air execution time and accuracy of the implemented ML solution. These models are …

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Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers Jan 2023

Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers

Browse all Theses and Dissertations

Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …

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Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi Jan 2023

Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi

Electronic Theses and Dissertations

Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans …

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Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani Jan 2023

Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani

Browse all Theses and Dissertations

Identifying the version of the Solidity compiler used to create an Ethereum contract is a challenging task, especially when the contract bytecode is obfuscated and lacks explicit metadata. Ethereum bytecode is highly complex, as it is generated by the Solidity compiler, which translates high-level programming constructs into low-level, stack-based code. Additionally, the Solidity compiler undergoes frequent updates and modifications, resulting in continuous evolution of bytecode patterns. To address this challenge, we propose using deep learning models to analyze Ethereum bytecodes and infer the compiler version that produced them. A large number of Ethereum contracts and the corresponding compiler versions is …

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The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii Jan 2023

The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii

Browse all Theses and Dissertations

The widespread expansion of Electric Vehicles (EV) throughout the world creates a requirement for charging stations. While Cybersecurity research is rapidly expanding in the field of Electric Vehicle Infrastructure, efforts are impacted by the availability of testing platforms. This paper presents a solution called the “Open Charge Point Protocol (OCPP) Cyber Range.” Its purpose is to conduct Cybersecurity research against vulnerabilities in the OCPP v1.6 protocol. The OCPP Cyber Range can be used to enable current or future research and to train operators and system managers of Electric Charge Vehicle Supply Equipment (EVSE). This paper demonstrates this solution using three …

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A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham Jan 2023

A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham

Browse all Theses and Dissertations

The Industrial Internet of Things (IIoT) refers to a set of smart devices, i.e., actuators, detectors, smart sensors, and autonomous systems connected throughout the Internet to help achieve the purpose of various industrial applications. Unfortunately, IIoT applications are increasingly integrated into insecure physical environments leading to greater exposure to new cyber and physical system attacks. In the current IIoT security realm, effective anomaly detection is crucial for ensuring the integrity and reliability of critical infrastructure. Traditional security solutions may not apply to IIoT due to new dimensions, including extreme energy constraints in IIoT devices. Deep learning (DL) techniques like Convolutional …

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Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir Jan 2023

Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir

Electrical and Computer Engineering Publications

In recent years, electric vehicles (EVs) have been widely adopted because of their environmental benefits. However, the increasing volume of EVs poses capacity issues for grid operators as simultaneously charging many EVs may result in grid instabilities. Scheduling EV charging for grid load balancing has a potential to prevent load peaks caused by simultaneous EV charging and contribute to balance of supply and demand. This paper proposes a user-preference-based scheduling approach to minimize costs for the user while balancing grid loads. The EV owners benefit by charging when the electricity cost is lower, but still within the user-defined preferred charging …

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Two New Mathematical Models For Two Level Electricity Network Design With Distributed Generation, Burçi̇n Çakir Erdener, Berna Dengi̇z, Zülal Güngör, İmdat Kara Jan 2023

Two New Mathematical Models For Two Level Electricity Network Design With Distributed Generation, Burçi̇n Çakir Erdener, Berna Dengi̇z, Zülal Güngör, İmdat Kara

Turkish Journal of Electrical Engineering and Computer Sciences

In the new millennium, traditional electrical power systems have undergone a significant change driven by a set of requirements arising from evolving and changing technology. Thus, fundamental changes have occurred in the way electrical energy is produced, transmitted, and distributed. This situation has revealed the need to expand existing networks or to establish new networks. The available literature revealed that particular attention to the latter one is still limited due to the complexity of the power system. The purpose of this study is to contribute to the body of literature that tries to address the gap at overall design of …

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Bibliography, Huanjing Wang Jan 2023

Bibliography, Huanjing Wang

Faculty/Staff Personal Papers

Bibliography of publications by Huanjing Wang.

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Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee Jan 2023

Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee

Browse all Theses and Dissertations

This research explores data-driven AI techniques to extract insights from relevant medical data for pain management in patients with Sickle Cell Disease (SCD). SCD is an inherited red blood cell disorder that can cause a multitude of complications throughout an individual’s life. Most patients with SCD experience repeated, unpredictable episodes of severe pain. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting the patient’s pain intensity level due to the subjective nature of pain. In this study, we leverage multiple data-driven AI techniques to improve pain management in patients with SCD. The proposed approaches …

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A Novel Knowledge-Based Federated Deep Learning Approach For Enhancing Security And Privacy Preservation In Iot Edge Computing Applications, Tabassum Simra Jan 2023

A Novel Knowledge-Based Federated Deep Learning Approach For Enhancing Security And Privacy Preservation In Iot Edge Computing Applications, Tabassum Simra

Browse all Theses and Dissertations

The Internet of Things (IoT) infrastructure encompasses smart devices and real-time sensors connected through the Internet, facilitating the exchange of large datasets among these devices. This interconnected network of IoT sensors generates a significant volume of data for processing and analysis by embedded IoT Edge Computing systems. IoT Edge Computing systems enable efficient real-time analysis and data communications. Furthermore, IoT Edge Computing emerges to enhance the overall efficiency of IoT applications, making them adept at handling the dynamic demands of AI-based and large data-driven applications. The integration of IoT Edge Computing introduces several unique research challenges. Unfortunately, IoT Edge Computing …

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