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Combining Fuzzy Logic and Reinforcement Learning for Resource Management in Edge computing 5

Combining Fuzzy Logic and Reinforcement Learning for Resourc...

引用

5th international conference on Electronics and Sustainable communication Systems, ICESC 2024

作者： Prasath, S. Ram Selvi, M. Krishnan, R. Santhana Nithila, Ezhil E. Malar, P. Stella Rose Sankar, G. Ram Scad College of Engineering and Technology Computer Science and Engineering Cheranmahadevi India Rajarajeswari College of Engineering Computer Science and Engineering Bangalore India Scad College of Engineering and Technology Electronics and Communication Engineering Chranmahadevi India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Electronics and Communication Engineering Chennai Avadi India J.P. College of Engineering Electronics and Communication Engineering Thenkasi India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798350379945

With the wide spread of Internet of Things (loT) devices, edge computing plays a decisive part in meeting the computational demands of loT applications. Efficient resource allocation in such networks is essential to ensure optimal utilization of resources and meet the quality of service (QoS) necessities of loT applications. This research addresses the challenge of dynamic resource allocation in edge computing networks for loT applications through a novel hybrid AI approach, 'FledegeRL.' By integrating fuzzy logic and reinforcement learning, FledegeRL aims to optimize resource utilization and enhance system performance. The proposed framework is evaluated through simulation analysis and compared with existing algorithms, including Q-Iearning, Fuzzy Logic control, and Ant Colony Optimization, using metrics such as resource allocation accuracy, average throughput, and network overhead. The results demonstrate that FledegeRL consistently outperforms these algorithms, achieving higher accuracy, greater throughput, and lower network overhead. This highlights the potential of FledegeRL as an effective solution for dynamic resource allocation in edge computing environments. © 2024 IEEE.

关键词： Quality of service

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CacheFlow: Enhancing Data Flow Efficiency in Serverless computing by Local Caching 14

CacheFlow: Enhancing Data Flow Efficiency in Serverless Comp...

引用

14th international conference on Cloud computing and Services Science, CLOSER 2024

作者： Ke, Yi-Syuan Wu, Zhan-Wei Tsai, Chih-Tai Lin, Sao-Hsuan Chou, Jerry Department of Computing Science National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9789897587016

In Serverless workflows, it is common for various functions to share duplicate files or for the output of one function to be the input for the following function. Currently, storing these files in remote storage is common, and transferring a large amount of data over the network can be inefficient and time-consuming. However, the state of the art has not yet optimized this aspect, resulting in time wastage. In this paper, we present an improved data transfer solution that reduced data transfer time by up to 82.55% in our experiment. This improvement is achieved by replacing the time spent on remote network access with local disk access time. To reduce the data transfer route, we implement per-node caching, utilizing disk storage as a local cache space. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Data transfer

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Image Processing Based Automatic Traffic control System

Image Processing Based Automatic Traffic Control System

引用

2024 international conference on Innovative computing, Intelligent communication and Smart Electrical Systems, ICSES 2024

作者： Ponnuru, Sudhakiran Sharma, Ambrish Kumar Khan, Patan Feridoz Poovannan, E. Lakshmi, B. Venkata Gopinath, S. New Horizon College of Engineering Department of Ece Karanataka Bangalore India Noida Institute of Engineering and Technology Department of Mca Greater Noida India School of Computing Mohan Babu University Department of Cse Andhra Pradesh Tirupati India Saveetha Engineering College Department of Ece Tamil Nadu Chennai602105 India Department of humanities YSR Kadapa India Gnanamani College Of Technology Tamilnadu Namakkal637018 India

ISBN: (纸本)9798331543617

As the number of people living in cities increases and more people drive, one of the most important problems is traffic congestion. An intelligent system that could effectively manage traffic congestion based on traffic density was required due to the rise in the number of cars. While current traffic management systems operate using fixed time-based methodologies, conventional traffic control systems are unable to manage the complicated traffic flow at junctions. There are numerous methods for establishing effective traffic control systems in urban areas. However, no method exists that is effective in real-time, and no system is prepared to accept changes on a constant basis. Using a digital image processing tool in MATLAB and the image processing technique known as morphological operations, the real-time traffic management system determines the percentage match to control the flow of traffic. By use MATLAB code that modifies the green, yellow, and red-light times in relation to traffic volume and density. To enhance its robustness and reliability the proposed traffic control system which is based on image processing also integrates advanced features such as scenarios involving emergency vehicles. © 2024 IEEE.

关键词： Traffic congestion

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Research on Enhancing Security in Critical control Operations of Power Systems through End-to-End Trusted Connection Algorithm 24

Research on Enhancing Security in Critical Control Operation...

引用

9th international conference on Intelligent Information Processing, ICIIP 2024

作者： Wang, Fen Yue, Xiaoguang Wuhan Engineering Science and Technology Research Institute China European University Cyprus

ISBN: (纸本)9798400718076

This study aims to address the issue of end-to-end trusted connections in critical control operations of power systems, particularly in complex environments spanning multiple trust domains. With the accelerated digital transformation of power systems, traditional security measures have become inadequate to counter increasing cybersecurity threats, especially in terms of ensuring the safety and reliability of critical control *** research proposes a novel method based on trusted state attestation and trusted connection authentication technologies. By leveraging trusted computing node authentication and connection techniques, the study ensures that computing nodes across different trust domains can establish fully secure, end-to-end trusted connections. A reliable connection architecture is constructed using cryptographic algorithms provided by trusted hardware modules (e.g., trusted boards or chips), and end-to-end encryption authentication components are *** proposed technologies have been validated in real-world power systems. The deployment of the trusted network connection platform and client significantly enhances the security and reliability of critical control operations in power systems, effectively addressing the issue of secure communication between multiple *** results demonstrate that trusted state attestation and trusted connection authentication technologies effectively improve secure communication capabilities in cross-domain power systems, significantly enhancing the security and overall reliability of critical control operations. This approach provides essential theoretical and practical support for improving the security of future power systems. © 2024 Copyright held by the owner/author(s).

关键词： Authentication Protocol

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A Novel Approach for Underwater Image Enhancement Using Style Transfer Technique 5

A Novel Approach for Underwater Image Enhancement Using Styl...

引用

5th international conference on control, communication and computing, ICCC 2023

作者： Anil, Adithya Divya Prasad, K.H. Sreelatha, G. College of Engineering and Technology Dept. of Electronics and Communication Trivandrum India

ISBN: (纸本)9798350334128

In ocean engineering and research, underwater imaging is a developing field. Usually, underwater images exhibit low contrast, distorted colour, and blurred features due to factors like refraction, absorption, and scattering of light by water-borne suspended particles. In order to address these challenges, we have proposed a novel style transfer based deep learning approach for the enhancement of underwater images. The suggested method consists of two stages: i) segmentation stage and ii) enhancement stage. The segmentation stage is implemented using SUIM-Net, which does the semantic segmentation of underwater images. The second stage is the enhancement stage, where we use a style transfer technique, which consists of an encoder-decoder circuit with whitening and coloring transforms. It also uses wavelet pooling which preserves the structural features while stylizing the distorted underwater images. These aids in reconstructing the signals more accurately. To evaluate the performance of the suggested method, various metrics such as Structural Similarity Index (SSIM), Peak Signal to Noise Ratio (PSNR), Underwater Image Quality Measure (UIQM) and Underwater Color Image Quality Evaluation (UCIQE) are used. Better UIQM values were obtained using the suggested method when it was compared to other cutting-edge methodologies. © 2023 IEEE.

关键词： Semantic Segmentation

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Design of Fault Monitoring Algorithm for Electrical automation control Equipment Based on Multi-Sensor

Design of Fault Monitoring Algorithm for Electrical Automati...

引用

international conference on Artificial Intelligence and communication Technologies, ICAICT 2023

作者： You, Xiao-Rong ChongQing Industry and Information Vocational College Chongqing China

ISBN: (纸本)9789819969555

A single sensor can only monitor a single state or environmental parameter. The operation of electrical automation control equipment conforms to the barrel effect, that is, a certain factor exceeds the maximum operating limit that electrical automation control equipment can bear, and the fault will inevitably occur. The basic purpose of information fusion is to make full use of multiple sensor resources. Based on multi-sensor data fusion technology, this paper introduces data fusion technology into the field of fault monitoring of electrical automation control equipment. An end-to-end adaptive fault monitoring algorithm for electrical automation control equipment is proposed based on multi-head attention mechanism and CNN (Convolutional Neural Network). This algorithm has stronger robustness and, combined with CNN, improves the accuracy of network fault classification. The research results show that when the signal-to-noise ratio of the noise signal is 7 dB, the accuracy of multi-attention CNN prediction has reached 97% and has remained at 100% since then. The experimental results show that the multi-attention CNN algorithm has better noise adaptability and stronger robustness in noise interference environment compared with other mainstream algorithms. The fault monitoring algorithm of electrical automation control equipment proposed in this paper can help share the work pressure of staff. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Adaptive control systems

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AI for Predicting Solar Flare and Study it's Effects on Earth's Temperature

AI for Predicting Solar Flare and Study it's Effects on Eart...

引用

2024 international conference on System, Computation, automation and Networking, ICSCAN 2024

作者： Mandal, Binod Sah, Arun Kumar Umamageswaran, J. Amrita School of Computing Department of Cse Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9798331510022

Solar flare one of the most discussing events in space science is intense bursts of electromagnetic radiations emitted from sun. This phenomena has significant impact on space weather and can influence various earths systems including atmospheric temperatures. Not only this solar radiations have severe impacts on satellite operations, communication system and power grids. This research paper aims to present novel approach for predicting solar flare using Recurrent Neural Network (RNN) architectures. In the paper we have proposed Long Short-Term Memory (LSTM) networks and Gated Recurrent Units (GRU) to forecast energy magnitude (keV). Our methodology includes hyper-parameter tuning and use of custom weighted loss function to enhance model accuracy and performance to 88.36%. The datasets used in the study is taken from SHARP summary parameters obtained form vector magnetograms captured by the HMI on the Solar Dynamics Observatory (SDO). This study consists of two modules, the first module is predicting solar flare energy magnitude and second module is to find study how these flare have impacts on temperature. © 2024 IEEE.

关键词： Atmospheric temperature

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Efficient 3D Multi-View Multi-Object Tracking with Labeled Multi - Bernoulli Approximation 13

Efficient 3D Multi-View Multi-Object Tracking with Labeled M...

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13th international conference on control, automation and Information Sciences, ICCAIS 2024

作者： Dat Nguyen, Tran Thien Van Nguyen, Hoa Shim, Changbeom Nguyen, Viet Choi, Hyunjin School of Electrical Engineering Computing and Mathematical Sciences Curtin University Australia Ai R and D Center Aibiz Co. Ltd. Seoul Korea Republic of

ISBN: (纸本)9798331542047

In this paper, we propose an efficient algorithm for 3D multi-view multi-object tracking. The method is based on labeled multi-Bernoulli approximation of a state-of-the-art 3D visual tracking based on generalized labeled multi-Bernoulli filter. Compare to the baseline, our method demonstrates the improved efficiency on real 3D pedestrian tracking datasets. If the detection quality is high, the tracking accuracy of our method is comparable to the baseline. Our source codes will be published at https://***/TranThienDat-Nguyen/3D-VisualTracking. © 2024 IEEE.

关键词： 3D visual tracking multi-sensor data fusion multi-view multi-object tracking

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Enhancing Performance of CUDA Quicksort Through Pivot Selection and Branching Avoidance Methods 29

Enhancing Performance of CUDA Quicksort Through Pivot Select...

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29th international conference on Information, communication and automation Technologies, ICAT 2023

作者： Catic, Irvin Mujic, Mehmed Nosovic, Novica Hrnjic, Tarik University of Sarajevo Faculty of Electrical Engineering Department of Computing and Informatics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350399837

This paper presents a fine-tuned implementation of the quicksort algorithm for highly parallel multicore NVIDIA graphics processors. The described approach focuses on algorith-mic and implementation-level improvements to achieve enhanced performance. Several fine-tuning techniques are explored to identify the best combination of improvements for the quicksort algorithm on GPUs. The results show that this approach leads to a significant reduction in execution time and an improvement in algorithmic operations, such as the number of iterations of the algorithm and the number of operations performed compared to its predecessors. The experiments are conducted on an NVIDIA graphics card, taking into account several distributions of input data. The findings suggest that this fine-tuning approach can enable efficient and fast sorting on GPUs for a wide range of applications. © 2023 IEEE.

关键词： Sorting

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A novel decentralized control strategy for microgrids, combining renewable energy resources 2

A novel decentralized control strategy for microgrids, combi...

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2nd IEEE international conference on Electrical, automation and Computer Engineering, ICEACE 2024

作者： Yu, Zhe Wang, Zhenqi Kou, Jinchi State Grid Benxi Electric Power Supply Company Benxi117000 China

ISBN: (纸本)9798350368208

The expanding integration of Renewable Vitality Assets (RERs) into conveyance systems comes about in Organized Renewable Vitality Assets (NRERs). The agreeable Peer-to-Peer (P2P) control design completely leverages NRERs' vigor and versatility. This work presents a multi-agent framework for P2P control of the NRERs-based Web of Things (IoT). The regulative framework is completely disseminated and comprises of two control layers that are worked by the specialist of each RER. For essential control, each RER-agent employments a hang control to share control locally. For auxiliary control, a dispersed dissemination procedure is recommended that permits RERs to share self-assertive control. A disseminated real-time sharing control procedure is given as an imperfect arrangement to the compelled stochastic programming issue that does not require any framework measurements. The Web Convention (IP)/Transmission control Convention (TCP) is utilized at the neighborhood communication level, whereas the Message Lining Telemetry Transport (MQTT) convention is utilized universally. The adequacy of the suggested framework is approved by numerical recreation utilizing the altered IEEE 9 hub test feeder. A few scenarios are developed based on framework stack sorts, with private structures and little commercial outlets. The recreation comes about affirmed the possibility and viability of the proposed method for the MGs' differing working circumstances. © 2024 IEEE.

关键词： Stochastic programming

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