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Dueling Double DQN with Attention for Optimized Offloading in Wireless-Powered Edge-Enabled Mobile computing Networks

Dueling Double DQN with Attention for Optimized Offloading i...

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2024 IEEE international conference on Big Data, BigData 2024

作者： Tripathi, Shivani Kumar, Praveen Chaitanya, Mailram Sai Teja, Nagireddy Sai Tarun Misra, Rajiv Singh, T.N. Indian Institute of Technology Patna Department of Computer Science and Engineering Patna India B.P Mandal College of Engineering Madhepura Department of Computer Science and Engineering Bihar Madhepura India Indian Institute of Technology Patna Department of Civil and Environmental Engineering Patna India

ISBN: (纸本)9798350362480

This research work introduces a new strategy to enhance computation offloading in wireless-powered Edge-Enabled Mobile computing (EEMC) networks by utilizing Dueling Double Deep Q-Networks with Attention (Dueling DDQN-A). EEMC facilitates the offloading of computational tasks from mobile devices to local edge servers, leading to decreased latency and improved energy efficiency. However, the dynamic and stochastic nature of wireless environments presents significant challenges for real-time task offloading decisions. To address this, we enhance the Dueling DDQN framework by integrating an attention mechanism to prioritize the most relevant features in the state space. The proposed Dueling DDQN-A model enhances decision-making by separating state value estimation from action advantage estimation. Additionally, the model uses attention to prioritize key state features, leading to improved adaptability in dynamic wireless channel and network environments. We frame the offloading decision problem as a Markov Decision Process (MDP) and apply deep reinforcement learning to optimize both the computation rate and energy efficiency. We compare and evaluate the model through comprehensive simulations using the latest techniques like Simple DQN, Double DQN, and Dueling DDQN. Our results demonstrate that Dueling DDQN-A achieves a 59.12% improvement in average computation rate and a 16.19% reduction in energy consumption over the baseline models. Additionally, it significantly outperforms the baselines in terms of training loss and convergence speed. These findings suggest that Dueling DDQN-A offers a robust and highly efficient solution for real-time computation offloading in wireless-powered EEMC networks, making it a strong candidate for deployment in real-world scenarios. © 2024 IEEE.

关键词： Stochastic systems

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Preliminary Design of Hybrid Simulation Framework for Workload Analysis in Automotive Edge computing

Preliminary Design of Hybrid Simulation Framework for Worklo...

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international conference on Information and Communication technology convergence (ICTC)

作者： JiHyun Kwon SangEun Park Hoon Sung Chwa Jeongho Kwak Ji-Woong Choi BaekGyu Kim Dept. of Electrical Engineering and Computer Science DGIST Daegu South Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Many vehicular tasks shall be completed in a timely manner as they move. In automotive edge computing, a vehicle can offload such tasks to an edge server in proximity to process them faster than using the cloud computing model. However, such an edge server has limited communication coverage and relatively smaller computing power compared to the general cloud server, it is important to distribute the offloaded workloads appropriately. One needs to understand such workload patterns and quantitatively analyze them for such workload distribution. We propose a preliminary hybrid simulation framework that generates compute workloads via a combination of the virtual vehicular traffic and the physical edge-server platforms.

关键词： Geometry Cloud computing Roads Hybrid power systems Hardware Information and communication technology Servers Edge computing Automotive engineering convergence

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PyMatching-based Decoding Simulation of Rotated Surface Codes in Classical Quantum Simulator 13

PyMatching-based Decoding Simulation of Rotated Surface Code...

引用

13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Lee, Sang-Min Jin, Ki-Sung Cha, Gyu-Il Electronics and Telecommunications Research Institute Cloud Computing Sw Research Center Daejeon Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

PyMatching provides a method for decoding quantum errors using the minimum-weight perfect matching algorithm. However, although the PyMatching supports various quantum error correction codes, no deep study has been conducted on the rotated planar surface codes that are receiving the latest attention. In this study, we define a procedure for detecting errors using PyMatching for rotated planar surface codes and analyze the correctness of error correction results. To compare error correction behavior by logical qubit size, we used logical qubit with distances of 3, 5, and 7, respectively. Furthermore, we have conducted comparative empirical studies by comparing the theoretical predictions of PyMatching with the actual execution results of classical state vector simulators. © 2022 IEEE.

关键词： Error correction

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Fraction Order PID Controlled Single Phase Electric Vehicle Charger with Quadratic Boost Converter 3

Fraction Order PID Controlled Single Phase Electric Vehicle ...

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3rd international conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Balaji, B. Hemalatha, P. Krishnaraj, S. Ashraf, Z. Yaseen Dept. of EEE IFET College of Engineering Villupuram India TIFAC-CORE in Cyber Security Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798331532420

This research study proposes a novel strategy for charging Electric Vehicles through a combination of a Fractional Order Proportional-Integral-Derivative (FOPID) control scheme, a Single-Phase Electric Vehicle Charger (SPEVC) and a Quadratic Boost Converter. Towards the sustainable development of the nation, there is a growing demand for efficient charging mechanisms for electric vehicles. This work foresees an EV charging system that ensures high performance, reliability, and efficiency. It intermingles fractional calculus principles into control strategies. Also, it has the advantages of quadratic boost conversion which plays the primary role in the charging system. Additionally, it offers enhanced voltage gain and minimal stress on the components. This integration, in turn, increases the reliability and efficiency of the charging process. The proposed system overcomes the shortcomings of conventional integer-order PID controllers by giving maximal accuracy, enhanced robustness, and interference avoidance during the regulation of current and output voltage of converters’ output. This work highlights the wide-ranging experimental simulations and validations to verify SPEVC’s feasibility and validity. With these results, the complete assessment of FOPIC- the FOPIC-controlled charging system is carried out under various payload factors and input voltage oscillations. Various performance metrics are considered for validating the proposed system against convergence time, peak, and residual error. Experimental results show that the proposed system outperforms traditional systems. Moreover, the findings are composed to enhance the EV charging mechanism by unveiling an efficient, dynamic, and resilient control strategy. Finally, this system promises to break through EV charging technology by coping with the challenges in charging architectures, accordingly promoting diversified EV adoption through electrical grid resilience and energy optimization. © 2024 IEEE.

关键词： Three term control systems

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Stochastic Differential Equation of the Quantization based Optimization 13

Stochastic Differential Equation of the Quantization based O...

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13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Seok, Jinwuk Cho, Changsik Electronics and Telecommunications Research Institute Next-Generation System Sw Research Section Future Computing Research Division Artificial Intelligence Research Laboratory Daejeon Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

We propose a stochastic differential equation for a quantization-based optimization algorithm. A fundamental differential equation describes the state transition by an algorithm to analyze the dynamics of an optimization algorithm. According to the White Noise Hypothesis of quantization error with dense and uniform distribution, we can regard the quantization error as an identically independent distribution(i.i.d.) white noise. It leads that we can obtain a stochastic equation about the quantization-based optimization algorithm to analyze the global dynamics. Numerical experiments show that the proposed algorithm involves better performance than the conventional optimization algorithm, such as simulated annealing. © 2022 IEEE.

关键词： Global optimization

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Leveraging Industrial IoT Infrastructure for Remote Sensing and Edge computing in the Mining Sector 5

Leveraging Industrial IoT Infrastructure for Remote Sensing ...

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5th international conference in Electronic Engineering, Information technology and Education, EEITE 2024

作者： Eleftherios, Emmanouil Papatsaroucha, Dimitra Markakis, Evangelos K. Hellenic Mediterranean University Electrical and Computer Engineering Heraklion Greece

ISBN: (纸本)9798350372878

Mining 4.0 signifies a paradigm shift within the mining sector and is defined as an all-encompassing strategy for industry revolution by optimizing mining processes through the utilization of digital technologies, automation, and data analytics to streamline processes. Mining 4.0 aims to develop intelligent and networked mining systems that enhance resource utilization, improve operational efficiency, reduce costs, and mitigate environmental harm, all while prioritizing the safety and welfare of workers. The process of mining digitization encompasses the methodical collection, management, and monitoring of data derived from diverse sources, including sensors, equipment, vehicles, and more. It permits remote, realtime monitoring of environmental and operational conditions, as well as the integration of control systems designed to optimize and automate processes. With digital transformation, the mining sector aspires to overcome conventional obstacles and adjust to changing market requirements, therefore facilitating a more sustainable and efficient future. A critical challenge in the process of digitizing the mining sector is the need to provide reliable routes for transmitting and communicating data between physical and digital components within mining environments. This paper examines the convergence of Mining 4.0 and mining digitization, with a specific emphasis on the pivotal role that remote sensing, edge computing, and decentralized communication systems play in data transmission and real-time monitoring in light of enhancing mining operations' safety and efficiency. The study performed puts forward a European solution based on open standards and tools, revolving around an Industrial Internet of Things (IIoT) Gateway that is a core component of the proposed communication system. This gateway will function as an intermediary between the edge and cloud-based platforms and will facilitate real-time monitoring through the establishment of resilient wireless communi

关键词： Gateways (computer networks)

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Artistic Transformation Of Architectural Images Using Neural Style Transfer 15

Artistic Transformation Of Architectural Images Using Neural...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Natesan, P. Harini, M. Kasthuri, Chitrasena Nehru Deepankumar, G. Kongu Engineering College Department of Information Technology Perundurai India

ISBN: (纸本)9798350370249

In recent years, the convergence of computational artistry and architectural visualization has led to innovative techniques for infusing artistic styles into architectural imagery. This paper explores the fascinating intersection of art and architecture through the application of neural style transfer algorithms to urban landscapes and architectural compositions. Traditional image editing procedures or hand painting represent examples of style transfer methods with severe limitations. When applying style transfer to architectural images, structural details may be lost due to an overemphasis on artistic style, leading to unrealistic texture application and visual incoherence. Color distortion and the risk of the style overpowering the architectural content further compound these challenges. Additionally, inadequate hyperparameters may result in a loss of contextual understanding, where the algorithm fails to grasp architectural significance, leading to visually confusing compositions. In this work, various pre-trained models of CNN(Convolutional Neural Network) and their hyperparameters are compared. The study aims to evaluate the impact of different hyperparameters, such as style weight, content weight, and learning rate, on the quality and fidelity of stylized images. By systematically varying these hyperparameters and analyzing their effects on the output images, this research aims to identify the optimal combination that maximizes style transfer fidelity while preserving content details. Content preservation, geometric distortion, artifact reduction, and visual quality are important criteria for comparison. Metrics like the Peak Signal-to-Noise Ratio (PSNR), the Structural Similarity Index (SSI), and others are used to statistically assess these properties. The research attempts to determine the best pre-trained CNN model and the best hyperparameters for style transfer that are most suitable for architectural images. © 2024 IEEE.

关键词： Convolutional neural networks

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Scalable Ddos Attack Detection in Cloud computing Using Neural Networks 4

Scalable Ddos Attack Detection in Cloud Computing Using Neur...

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4th IEEE international conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Sharmila, P. Baxi, Paramjit Thomas, Shaji Borade, Monali Ravindra Vijayshankar, G.R. Mishra, Mukul Prince Shri Venkateshwara Padmavathy Engineering College Department of S&h Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India Karnataka Bangalore India Vishwakarma Institute of Technology Pune India Karpagam Academy of Higher Education Department of Civil Engineering Coimbatore641021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India

ISBN: (纸本)9798331518981

In a Distributed Denial of Service (DDoS) assault, hackers sneakily insert malicious data packets into client networks' internet traffic, causing a catastrophic outage for end users in a cloud computing environment. This is a major issue with cloud computing as detecting and mitigating intrusions is a difficult operation that will impact the whole architecture's functioning. In order to construct machine learning algorithms that can correctly and efficiently detect intrusions, rigorous literature studies are conducted to explore different machine learning approaches, neural network models, and optimization algorithms. The goal is to discover any gaps or flaws and then create these algorithms. Intrusion detection tactics based on Back Propagation Neural (BPN) and Multi-layer Perceptron (MLP) are created in the ANN model to identify DDoS. This paper proposes a hybrid optimization method that combines the exploration and exploitation capabilities of PSO and HHO in order to achieve performance. The suggested hybrid optimiser successfully addresses the drawbacks of traditional algorithms, including the problems of local stagnation, delayed convergence, and optimum trapping of both the local and global levels. The neural network models' weight and bias variables are fine-tuned using the suggested hybrid Harris Hawks Optimization and Particle Swarm Optimization (HHO-PSO) method, which is also used for feature selection. The suggested technique, HHO-PSO with BPN, has a 95.73 percent success rate. When compared to MLP, BPN, and HHO-PSO with MLP, alternative approaches exhibit poorer accuracy, precision, and recall levels that are reflected by their respective F1 ratings. The suggested hybrid method, on the other hand, shows that it is more effective than these models. © 2024 IEEE.

关键词： Denial-of-service attack

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An Interactive E-Learning Tool 7

An Interactive E-Learning Tool

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7th IEEE international conference for convergence in technology, I2CT 2022

作者： Kodagoda, D.G. Ishara, K.G.R.U. Kumara, R.M.R.P. Dilshan, W.A.D.T. Weerasinghe, Lakesha Premadasa, Nadeesa Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9781665421683

Use of E-learning systems has surged immensely during the Covid-19 pandemic, which started around 2020. This research specifically conducted to introduce novel features with the purpose of enhancing traditional E Learning platforms. The suggested features are namely, avoid unauthorized users from accessing private video sessions using face recognition, manipulating 3D objects by hand gestures, analyzing student's attention using face landmarks, smart QAs using voice recognitions. These features will provide not only an enhancement for e-Learning platforms but also it will improve user experience, efficiency, and effectiveness of current tools up to a certain distinguishable level. © 2022 IEEE.

关键词： Face recognition

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Unknown Disturbance Estimator Based Adaptive Nonsingular Fast Terminal Sliding-Mode Control for n-DOF Nonlinear Robotic Systems

Unknown Disturbance Estimator Based Adaptive Nonsingular Fas...

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2024 international conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Duan, Ziyu Tian, Yang Wang, Haoping Ahmed, Saim Azar, Ahmad Taher Ben Njima, Chakib Nanjing University of Science and Technology Nanjing China Prince Sultan University College of Computer and Information Sciences Riyadh11586 Saudi Arabia Riyadh Saudi Arabia Benha University Faculty of Computers and Artificial Intelligence Benha Egypt University of Sousse Tunisia

ISBN: (纸本)9798350361025

This paper develops an improved second-order filter unknown disturbance estimator (UDE) with adaptive nonsingular fast terminal sliding mode control (ANFTSMC) to solve the trajectory tracking problem of uncertainties and external disturbances in robotic system. The developed UDE -ANFTSMC controller not only uses the advantages of NFTSM theory to ensure fast convergence speed, avoid singularity and robustness to uncertainties and external disturbances, but also uses UDE to estimate and suppress unknown disturbances in the system. Firstly, UDE is introduced, and then the ANFTSM control scheme is designed with a NTFSM surface. Lyapunov stability theory was used for stability analysis, and the manipulator mathematic model and SolidWorks' prototype were used to demonstrate the effectiveness of the proposed control scheme. © 2024 IEEE.

关键词： Sliding mode control

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