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检索条件"任意字段=Conference on Internet Quality and Performance and Control of Network Systems"

共 10553 条记录，以下是541-550 订阅

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Event-Triggered single-network control for Nonlinear Continuous-Time Zero-Sum Games with Partially Unknown Dynamics 1

Event-Triggered single-network Control for Nonlinear Continu...

引用

1st International conference on Cyber-Energy systems and Intelligent Energy, ICCSIE 2022

作者： Peng, Binbin Cui, Xiaohong Wan, Zimeng Yu, Haijiao China Jiliang University The College of Mechanical and Electrical Engineering Hangzhou China China Jiliang University Key Lab. of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province Hangzhou China

ISBN: (纸本)9781665452151

This paper proposes an event-triggered integral reinforcement learning algorithm to solve the Hamilton-JacobiIsaacs (HJI) equation related to the zero-sum game problem. Then, we design a triggering rule to constrain the control updates. Secondly, the HJI partially differential equation is approximately solved using a single-critic neural network structure. The control law and disturbance law are modified when an event occurs. The system state and the network weights error are uniformly ultimately bounded (UUB) by Lyapunov theory. Finally, an engineering example is utilized to confirm the performance of the algorithm. © 2023 IEEE.

关键词： Reinforcement learning

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International conference on Electrical and Electronics Engineering, ICEEE 2023

International Conference on Electrical and Electronics Engin...

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International conference on Electrical and Electronics Engineering, ICEEE 2023

ISBN: (纸本)9789819986606

The proceedings contain 49 papers. The special focus in this conference is on Electrical and Electronics Engineering. The topics include: Comparative Study of Different Grid Connected Wind Generator;photovoltaic with Battery and Supercapacitor Energy Storage System for Better performance Devices and Modelling;optimal Planning of Hydrogen Refueling Stations Considering Balanced Utilization of Resources;a Communication Technique to Improve the performance of On Load Tap Changer of Transformer with Renewable Load;performance Analysis of Wind Power Forecasting via System Advisor Model Software;performance of Fuzzy MPPT for a Distributed Photovoltaic System Under Changing Environmental Condition;enhancing Photovoltaic Connector Reliability: A Comparative Review of Studies with Practical Recommendations;a Comprehensive Study of Power quality Improvement Techniques in Smart Grids with Renewable Energy systems;Fault Detection at PCC Using Wavelet Theory in Grid-Tied Solar PV Battery-Based AC Microgrid;NSTLBO-Based Approach for Optimal Scheduling of Hydrothermal Generating Units in Regulated Environment;powering the Future: IoT-Enabled Smart Grids for Sustainable Energy systems;solar Charging Station for Electric Vehicles;Theoretical Analysis of Tandem Solar Cell Doped with MASnl3 with P3HT: PCBM Active Layer;Sensorless PMBLDC Motor control Strategies by Artificial Neural network (ANN) with PI controller;a Comprehensive Review on Electric Vehicle Battery Swapping Stations;Comparison Between PID and SMC controller to control the Speed of DC Separately Excited Motor;implementation and Evaluation of a Secure Keyless Ignition and Integrated control System for an Arduino-Based Instrumented Car;selection of Automated Guided Vehicles for Industrial Application Using Weighted Sum Method;Active Disturbance Rejection control of a SEPIC Converter.

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International conference on Electrical and Electronics Engineering, ICEEE 2023

International Conference on Electrical and Electronics Engin...

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International conference on Electrical and Electronics Engineering, ICEEE 2023

ISBN: (纸本)9789819982882

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Enhanced Ant Colony Optimization with Dynamic Evaporation Rate (EACO-DE): An Intelligent Congestion control System in IoV Environment

Enhanced Ant Colony Optimization with Dynamic Evaporation Ra...

引用

2023 IEEE International conference on Quantum Technologies, Communications, Computing, Hardware and Embedded systems Security, iQ-CCHESS 2023

作者： Sathishkumar, Sudarsan Amrishkanna, R. Nithya, B. Saranathan College of Engineering Dept. of Computer Science and Engg. Tamil Nadu Trichy620012 India National Institute of Technology Dept. of Computer Science and Engg. Tamil Nadu Trichy620015 India

ISBN: (纸本)9798350314946

internet of Vehicle (IoV) is a combined form of internet of Things (IoT) and Vehicular Ad-hoc network (VANET). Its fundamental goal is to increase the service quality of Intelligent Transportation System (ITS). The dynamic nature of IoV such as high dynamic topology, high mobility of vehicles, etc. are some of the factors that causes more congestion thus reducing the efficiency of routing. Many algorithms were designed to obtain the shortest path from the source to the destination. Choosing of Ant Colony Optimization (ACO) algorithm is one of the best ways to obtain the shortest path. In this paper, an Enhanced Ant Colony Optimization with Dynamic Evaporation rate (EACODE) algorithm is proposed to obtain the congestion-free optimized path which reduces the travel time, travel cost and traffic problems. Instead of fixed evaporation rate, it dynamic predicts the pheromone evaporation rate with the help of run time metrics to avoid the congested paths thus improving the efficiency of the travel. The simulation results show that the proposed EACO-DE algorithm improves the efficiency of the routing compared with primitive Ant Colony Optimization (ACO) algorithm and Enhanced Hybrid Ant Colony Optimization Routing Protocol (EHACORP) under various performance metrics. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Simulation and Optimization of a Techno-economic Virtual Power Plant Using CloudPSS DSLab 4

Simulation and Optimization of a Techno-economic Virtual Pow...

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4th Power System and Green Energy conference (PSGEC)

作者： Hu, Ran Yu, Zhitong Xiang, Yue Li, Bing Ma, Nan Huang, Zhanhua South China Univ Technol Sch Elect Power Engn Guangzhou 510640 Peoples R China Shenzhen Power Supply Bur Co Ltd Shenzhen 518000 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Tsinghua Sichuan Energy Internet Res Inst Chengdu 610213 Peoples R China

ISBN: (纸本)9798350365573;9798350365580

With the rapid advancement of renewable energy and flexible loads, such as electric vehicle, the structure of the power supply and load demand has undergone significant transformations. These changes have gradually shaped a new type of power system that primarily relies on renewable energy, integrates source, network, load, and storage synergistically, features active networks, and complements multi-energy systems. This shift has stimulated extensive research into virtual power plants (VPPs), which are capable of flexibly coordinating source and load resources. In this paper, a VPP is designed to optimize scheduling for a regional distribution network experiencing source-load imbalance. Initially, the CloudPSS DSLab platform is utilized to model distributed energy resources and the distribution power system. Subsequently, the DSLab SDK is employed to obtain the distribution system's boundary conditions, including forecasted load and tariffs. Finally, considering both technical and economic objectives, an intraday optimization model for the VPP is established, and optimized to derive an optimal scheduling strategy for power sharing and interaction among multiple VPPs, and feasibility of the operation strategy is verified through simulation. The optimization results demonstrate that the flexible scheduling of VPPs effectively reduces reverse transmission and increases the accommodation of the renewables in the distribution network, enhances the network's reliability, improves power quality, and amplifies economic performance.

关键词： CloudPSS DSLab Virtual power plant Distributed energy resource Optimization P2P

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Switch Migration Frequency for Load Balancing in Fog Computing Using Machine Learning Algorithm 8

Switch Migration Frequency for Load Balancing in Fog Computi...

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8th IEEE Asia Pacific conference on Wireless and Mobile, APWiMob 2023

作者： Fauzi, Mohd Husaini Mohd Ariffin, Sharifah Hafizah Syed Baharudin, Muhammad Ariff Yusof, Sharifah Kamilah Syed Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Malaysia

ISBN: (纸本)9798350327861

With the daily rise in internet usage due to affordable smart devices and easy access to advanced technologies, there is an increased strain on network cores, particularly from the internet of Things (IoT) traffic. Although this advancement aids in simplifying daily tasks, it leads to network congestion, demanding more robust network infrastructures. A promising solution lies in fog computing, a decentralised approach that brings cloud services closer to the network edge, aiming to enhance efficiency by reducing data transferred to the cloud. This solution boosts efficiency and addresses security and compliance concerns, especially with the exponential data challenges associated with IoT. Despite the benefits, an increase in connected devices results in a surge in network packets, potentially overburdening the fog environment. A viable response to this challenge is load balancing among fog nodes, mainly using switch migration, redirecting traffic from overloaded to underloaded controllers. However, frequent migrations may affect network latency and service quality. Implementing machine learning can potentially reduce migration frequency by forecasting traffic patterns. The experimental results suggest that the specific traffic characteristics within the network determine the need to minimise migration. In constantly high-traffic situations, a simple threshold approach is practical. At the same time, machine learning can optimise networks with variable traffic, with an 87%-100% reduction in migration frequency, avoiding unnecessary costs that impede performance. © 2023 IEEE.

关键词： internet of things

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Simulation of DDoS Attacks on LTE and LoRaWAN Protocols in the NS-3 network Simulator 12th

Simulation of DDoS Attacks on LTE and LoRaWAN Protocols in t...

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12th International conference on High-performance Computing systems and Technologies in Scientific Research, Automation of control and Production, HPCST 2022

作者： Baranov, Dmitry A. Terekhin, Aleksandr O. Bragin, Dmitry S. Mitsel, Artur A. Systems and Radioelectronics Tomsk State University of Control 46 Lenina Avenue Tomsk634050 Russia

ISBN: (纸本)9783031237430

The issue of creating a simulation model for conducting a DDoS attack on an information system is discussed in this paper. This system works on LTE and LoRaWAN protocols. According to the authors, this model makes it possible to evaluate the parameters of reliability and failure for data transmission channels under the influence of DDoS attacks. The evaluation was carried out when creating software and hardware systems for the internet of Things systems. The scenario proposed in the article makes it possible to create a new simulation model of a data transmission network. The process of initialization and configuration for the network elements of the LTE and LoRaWAN protocols is carried out. This solution allows us to level the disadvantages inherent in each of the protocols available in the simulator. There is also a description of the behavior of network attacks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data transfer

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IoT-Driven Water quality Management System using Deep Q-network 14

IoT-Driven Water Quality Management System using Deep Q-Netw...

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14th International conference on Information and Knowledge Technology, IKT 2023

作者： Rajabi, Shakiba Moghaddasi, Komeil Islamic Azad University Urmia Branch Department of IT and Computer Engineering Urmia Iran

ISBN: (纸本)9798350349412

The ongoing process of digital transformation is revolutionizing organizations across various sectors, leading to significant operational changes. This study introduces a novel IoT-based water quality management system, powered by advanced machine learning algorithms, to ensure the safety and well-being of individuals within organizations. The proposed system deploys strategically positioned IoT sensors within the water control center, continuously monitoring water quality parameters. These sensors detect a range of harmful substances, including chlorides, sulfates, nitrates, nitrites, heavy metals, iron, manganese, and hardness minerals. When pollutant levels exceed predefined thresholds, a Deep Q-network (DQN) algorithm is activated to assess the severity of the situation. By embracing digital transformation, organizations can enhance their ability to mitigate health risks and foster safer working environments. The system's real-Time monitoring, proactive alert mechanisms, and swift response capabilities showcase the advantages of leveraging digital technologies in revolutionizing water quality management practices. This study contributes to the ongoing digital transformation journey by demonstrating the practical implementation of smart, self-regulating systems to ensure water safety in organizational settings. © 2023 IEEE.

关键词： internet of things

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DDS-SLAM: Dense Semantic Neural SLAM for Deformable Endoscopic Scenes

DDS-SLAM: Dense Semantic Neural SLAM for Deformable Endoscop...

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2024 International conference on Intelligent Robots and systems

作者： Shan, Jiwei Li, Yirui Yang, Lujia Feng, Qiyu Han, Lijun Wang, Hesheng Shanghai Jiao Tong Univ Shanghai Engn Res Ctr Intelligent Control & Manag Dept AutomatKey Lab Marine Intelligent Equipment Key Lab Syst Control & Informat ProcMinist Educ Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9798350377712;9798350377705

Estimating camera motion and continuously reconstructing dense scenes in deformable environments presents a complex and open challenge. Many existing approaches tend to rely on assumptions about the scene's topology or the nature of deformable motion. However, these assumptions do not hold true in medical endoscopy applications. To address these challenges, we introduce DDS-SLAM, a novel dense deformable semantic neural SLAM that achieves accurate camera tracking, continuous dense scene reconstruction, and high-quality image rendering in deformable scenes. First, we propose a novel hybrid neural scene representation method capable of capturing both natural and artificial deformations. Additionally, by leveraging the 2D semantic information of the scene, we introduce a semantic loss function based on semantic distance fields. This approach guides network optimization at a higher level, thereby enhancing system performance. Furthermore, we validate our method through a series of experiments conducted on several representative medical datasets, demonstrating its superiority over other state-of-the-art approaches. The code is available at: https://***/IRMVLab/DDS-SLAM.

关键词： Endoscopy

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Real-Time Energy Efficient Communication for Large-Scale Industrial internet of Things 2nd

Real-Time Energy Efficient Communication for Large-Scale Ind...

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2nd International conference on Sustainability: Developments and Innovations, ICSDI 2024

作者： Khan, Musfira Khan, Muazzam A. Farman, Haleem Malik, Asad W. Ramzan, Muhammad Sher Islamabad Pakistan Department of Computer Science Quaid-I-Azam University Islamabad Pakistan ICESCO Chair for Big Data Analytics and Edge Computing Quaid-I-Azam University Islamabad Pakistan Smart Systems Engineering Lab College of Engineering Prince Sultan University Riyadh Saudi Arabia King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9789819783441

Industrial internet of Things (IIoTs) comprises large-scale sensors deployed to monitor and control the system. Deploying IoT devices presents challenges due to frequent disconnections and sudden power drainage in intermediate devices responsible for routing data. Consequently, the deployed network becomes sporadic, hindering connectivity with the industrial controller system, especially critical during emergencies. Furthermore, IoT node failures lead to a short network lifetime, which is intolerable in real-time industrial applications. This paper introduces a multi-hop clustering framework designed for reliable communication in industrial environments. The framework dynamically forms clusters, employing cluster heads and backup nodes to stabilize communication in the absence of a cluster head. Each cluster selects a backup node during the initial cluster head selection and later through data piggybacking. The proposed framework provides efficient communication across the IIoT network with the help of a backup and multi-hop clustering mechanism. The proposed framework is compared with two existing protocols i.e. cluster-based coordination routing (CRC) and energy-efficient quality of service routing (EEQSRP) protocols. The results show a considerable decrease in sensor energy consumption and packet delay. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Energy utilization

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