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UAV control in Multi-access Edge computing Using Markov Decision Process 1st

UAV Control in Multi-access Edge Computing Using Markov Dec...

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1st international conference on Intelligent Systems, Blockchain, and communication technologies, ISBCom 2024

作者： Elghitani, Fadi Fayed, Ibraheem M. National Telecommunication Institute Cairo Egypt

ISBN: (纸本)9783031823763

Cloud computing is the pradigim where service providers carry-on computational tasks for their customers. Multi-access Edge computing (MEC) is a recent form of service where the computational tasks are carried in a distributed manner at the edge of the network to be as close to customer as possible. This new pradigim have the advantage of lowering the latency, making the pradigim suitable for real-time applications. One promising way to deploy MEC is to mount the servers over a UAV which can be moved dynamically to become closer to users. In this paper, we address the challenges associated with UAV-mounted servers like energy consumption and path routing. We propose a UAV control mechanism based on continuous-time Markov Decision Process (CT-MDP). We demonstrated the advantage of the proposed mechanism in terms of task-satisfaction rate and policy computational time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Markov processes

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Challenge of Evolution to Cloud-Based control Systems with Aging Industrial Device communication Protocols

Challenge of Evolution to Cloud-Based Control Systems with A...

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control, Automation, and Instrumentation (IC2AI), international conference on

作者： Michael J. Anthony Technology & Innovation Rockwell Automation - Capitol Technology University Milwaukee WI USA

ISBN: (数字)9798331529604

ISBN: (纸本)9798331529611

This paper provides a future looking perspective on the evolution of cloud-native technologies in the design, operation, and maintenance of industrial control systems with aging device communication protocols. First a look at traditional control system design patterns and technologies before the Industry 4.0 shift. Then consider how advanced computing and networking power introduced with Industry 4.0 changed control systems in the past 10 years. Finally, a look at how the shift towards cloud-native technologies, big data processing, AI, and advanced computer-aided learning algorithms are challenged by the data modeling and transport norms of today's systems. This paper is a work in progress and draws no conclusions on the future. The purpose of this paper is to bring academic discussion into the needs for communication standardization in the evolving space of cloud-based control system design.

关键词： Cloud computing Technological innovation Protocols Industrial control Production Aerospace electronics control systems Data models Fourth Industrial Revolution Artificial intelligence

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In-depth development of temperature insensitive refractive index Fabry-Perot optical sensor 2

In-depth development of temperature insensitive refractive i...

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2nd international conference on Optical communication and Optical Information Processing, OCOIP 2024

作者： Gao, Yuda Luo, Yanhua Institute of Fiber Optics Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai200444 China

ISBN: (数字)9781510688995

ISBN: (纸本)9781510688988

Sensors based on optical fiber interference structures offer benefits such as high sensitivity, simple fabrication and good compatibility, and are widely used in fields like biological monitoring, chemical engineering, and environmental monitoring. However, these sensors often face unavoidable cross-sensitivity issues between temperature and refractive index. Therefore, developing a new optical fiber refractive index sensor that is insensitive to temperature and has a broad refractive index measurement range remains a significant research issue. In this work, proposing a temperature-insensitive refractive index sensor featuring a two-stage Fabry-Perot (F-P) cavity made from single-mode fiber (SMF), capillary fiber (CF), and no core fiber (NCF) based on the principle of mode interference. The research experimentally investigates the sensor's sensitivity to temperature and refractive index. Results indicate that the sensor's amplitude correlates linearly with the refractive index in both optical and Fourier domains, covering a refractive index range of 1.3164 to 1.4215. In the Fourier domains, sensitivities of - 0.7184/refractive index unit (RIU) and - 0.2672/RIU are recorded at two distinct positions, respectively. A direct relationship between the amplitude and the refractive index is established. Additionally, the proposed sensor is almost insensitive to temperature in both the wavelength and Fourier domains. At the same time, experimental validation using water, ethanol, isopropanol, and glycerin solutions with varying refractive indexes, yielding results that align well with the established refractive index relationship. © 2025 SPIE.

关键词： Fabry-Perot interferometers

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A Comprehensive End-to-End Solution for Web Security with Cryptography, Multi-Factor Authentication, and Secure communication 3

A Comprehensive End-to-End Solution for Web Security with Cr...

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3rd international conference on Intelligent Data communication technologies and Internet of Things, IDCIoT 2025

作者： Kumar, Kanderi Johith Sai, Kandlapalli Aravind Reddy, Adapala Dharshan Reddy, Chinthamreddy Pranay Daiwik Rajagopal, Shinu M. Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

In today’s digital landscape, securing sensitive information has become an essential priority in the modern digital era for both individuals and organizations. This project introduces a comprehensive web application that integrates advanced encryption and decryption functionalities alongside multifactor authentication (MFA) and secure payment processing. The application supports various cryptographic algorithms, including AES, DES, Triple DES, Blowfish, etc., allowing users to securely encrypt and decrypt data through dedicated routes accessed over secure HTTPS connections. To further enhance security, robust multifactor authentication mechanisms, such as OTP-based challenge-response and QR-code-enabled 2FA, have been implemented to prevent unauthorized access to sensitive operations. The platform also incorporates PGP encryption powered by Keybase, enabling users to securely exchange encrypted emails. Additionally, a secure payment gateway is integrated using Stripe, ensuring sensitive payment data is encrypted and handled safely. With a strong focus on data integrity, user privacy, and modern web security standards, this project delivers an all-encompassing solution for safeguarding sensitive information and facilitating secure communication. By addressing common vulnerabilities and security risks, the platform stands as a reliable and scalable tool for data protection. © 2025 IEEE.

关键词： Authentication Protocol

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Autonomous Indoor Navigation using Nav2 3

Autonomous Indoor Navigation using Nav2

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3rd international conference on Intelligent Data communication technologies and Internet of Things, IDCIoT 2025

作者： Sumathi, K. Ajay Balaji, L. Danaraj, A.P. Deepaganesh, M. Department of Electronics and Communication Engineering KIT-KalaignarKarunanidhi Institute of Technology Coimbatore India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

The project focuses on the design, development, and implementation of an Autonomous Mobile Robot (AMR) system specifically tailored for warehouse environments. The escalating demand for efficient warehouse management, driven by the e-commerce boom, necessitates the adoption of automated solutions to overcome challenges like labor shortages and operational inefficiencies. The proposed AMR system integrates advanced sensing technologies, including 2D LiDAR and IMU, with robust navigation and control algorithms to enable the robot to autonomously navigate through dynamic warehouse environments. The core of the system is built upon the ROS 2 framework, providing a robust and flexible platform for development and deployment. The project explores the implementation of Simultaneous Localization and Mapping (SLAM) techniques, utilizing the SLAM Toolbox, to enable the robot to build and update maps of its environment while simultaneously determining its position. Furthermore, the system incorporates advanced path planning algorithms and obstacle avoidance mechanisms to ensure safe and efficient navigation. The project utilizes Gazebo for realistic simulation and validation, allowing for thorough testing and optimization of the AMR system before real-world deployment. This research aims to contribute to the advancement of warehouse automation by developing a cost-effective and efficient AMR system that can significantly improve operational efficiency and productivity. © 2025 IEEE.

关键词： Motion planning

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Deep Learning Model with Optimization Strategies for DDoS Attack Detection in Cloud computing 3

Deep Learning Model with Optimization Strategies for DDoS At...

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3rd international conference on Intelligent Data communication technologies and Internet of Things, IDCIoT 2025

作者： Radhika, P. Kamalakkannan, S. Department of Computer Science Vel’s Institute of Science Technology and Advanced Studies Tamil Nadu Chennai India

ISBN: (纸本)9798331527549

Cloud computing (CC) remains as a chief research area for analysts because of its numerous applications and advantages. The dispersed nature of CC and its dependence on internet service poses several attacks and challenges. Mainly, the attacks like DDoS attempts to disrupt the online operations. Insider attacks cannot be detected using conventional detection techniques like firewalls. This study suggests a DDoS detection method for reducing the DDoS activity. The proposed work contributes under big data perspective by handling certain procedure for detection process. Data Generation phase is the initial step, and according to the work, DDoS dataset is considered under big data perspective. As the work is considered under the big data perspective, Map reduce (MR) framework is used, Mapper handles the data and process the feature extraction, which includes the extraction of raw features, Packet feature extractor, Improved Correlation and statistical Feature. Reducer provides the combined feature set. From the extracted feature set, appropriate features are selected via Weightage based Improved hybrid model combining the models like Long short term memory(LSTM) and Deep Maxout(DMO) networks is used. The weights of LSTM and DMO are optimally chosen using White Shark-Remora Optimization (WSROA) algorithm. Recursive Feature Elimination (RFE) process is used to precisely select the features for DDoS attack detection. The findings shows that the proposed hybrid bio-inspired algorithm outperforms with an accuracy of 94% compared to LSTM, Convolutional Neural Networks(CNN) and Deep Belief Networks(DBN). © 2025 IEEE.

关键词： Convolutional neural networks

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advanced Photonic Crystal Fiber Sensor Design For Efficient Air Pollution Detection

Advanced Photonic Crystal Fiber Sensor Design For Efficient ...

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2025 IEEE international Students' conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Barath Kumar, B. Hanush, B. Anbazhagan, Lavanya Faculty of Engineering and Technology Srm Institute of Science and Technology Department of Electronics and Communication Engineering 603203 India

ISBN: (纸本)9798331529833

This paper presents a novel approach for air pollution monitoring using Photonic Crystal Fiber (PCF) with unique optical properties. Through Finite Element Method (FEM) simulations in COMSOL, the study explores how the PCF's guiding characteristics are influenced by its geometric parameters at different wavelengths. The sensor, designed for enhanced sensitivity, selectivity, and fast response, focuses on detecting air pollutants. A microstructured core in the PCF enhances light-matter interaction, improving sensor performance. The optimized PCF structure ensures effective light confinement, enabling precise detection of environmental changes like temperature and refractive index variations. The results have significant potential for telecommunications, biomedicine, and environmental monitoring applications, contributing to advanced air pollution control technologies. © 2025 IEEE.

关键词： Environmental monitoring

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Knowledge-Defined Internet of Things Architecture for Cloud-Edge Collaborative Industrial Monitoring 24

Knowledge-Defined Internet of Things Architecture for Cloud-...

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2nd international conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Zhou, Hongyu Xing, Fangyuan Tong, Fei Wang, Mufeng Zhang, Yan Yang, Shuaifeng Southeast University Nanjing China China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798400710681

The Industrial Internet of Things (IIoT) has become a crucial technology driving the transformation of manufacturing towards intelligence. Traditional industrial networks primarily focus on data collection, whereas emerging IIoT emphasizes intelligent management and optimized control utilizing advanced technologies such as big data and artificial intelligence. With the more complex application scenarios, sole reliance on cloud computing fails to meet requirements for low latency and high security, thus leading to a trend towards edge-cloud collaborative computing. Knowledge-Defined Networking (KDN) introduces a knowledge plane above the control and data planes, which utilizes machine learning and deep learning methods to extract and analyze data and can guide the control plane in updating and optimizing network management and control decisions. This architecture enables the system to understand domain knowledge, supports knowledge-based reasoning decisions, and facilitates higher-level intelligent applications. This paper proposes a Knowledge-Defined Edge-Cloud Collaborative IoT architecture tailored for industrial monitoring scenarios. Therein, the edge is responsible for initial real-time data processing, while the cloud handles large-scale data storage and complex analytics. Knowledge definition are introduced into the entire framework and enables a comprehensive understanding of equipment status through historical data analysis and real-time feedback, which facilitates predictive issue identification and optimization of production plans. The enabling technologies that can implement the functions of the knowledge-based cloud, knowledge-based edge, knowledge-based end, and interfaces are summarized, which are expected to provide guidance for future IIoT. © 2024 Copyright held by the owner/author(s).

关键词： Cloud computing architecture

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Research on Storage Strategies for Multi-source Heterogeneous Subway Monitoring Data and Anomaly Detection technologies 24

Research on Storage Strategies for Multi-source Heterogeneou...

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14th international conference on communication and Network Security, ICCNS 2024

作者： Wang, Xinling Sun, Jinglai Zhang, Zhuxin Su, Yue Fang, Hui Liu, Hao Beijing Municipal Engineering Research Institute Beijing China North Automatic Control Technology Institute Shanxi TaiYuan China

ISBN: (纸本)9798400717994

This paper presents a comprehensive study on efficient storage strategies and anomaly detection techniques tailored for multi-source heterogeneous subway monitoring data. By leveraging advanced deep learning models, we aim to address the challenges posed by the vast amount, diversity, and complexity of data generated by modern subway systems. A novel framework is introduced, which integrates optimized data storage solutions with a deep neural network-based anomaly detection system. Experimental results on synthetic subway dataset demonstrate the effectiveness of our approach in terms anomaly detection accuracy. The proposed method achieves significant improvements over traditional methods, highlighting its potential for monitoring and predictive maintenance in subway systems. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Predictive maintenance

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Security Assessment of an LBP16-Protocol-Based Computer Numerical control Machine 18th

Security Assessment of an LBP16-Protocol-Based Computer Nume...

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18th international conference on Critical Infrastructure Protection

作者： Forihat, Yahya Taylor, Curtis Awad, Rima Asmar Ahmed, Irfan Virginia Commonwealth Univ Richmond VA 23284 USA Oak Ridge Natl Lab Oak Ridge TN USA

ISBN: (纸本)9783031818905;9783031818882;9783031818875

Subtractive manufacturing systems, specifically, computer numerical control machines, have revolutionized the manufacturing industry. Computer numerical control machining is the preferred method for producing finished parts due to its efficiency, speed and suitability for high-volume production. Securing computer numerical control machines is a priority. Compromises or disruptions of these machines can result in significant downtime, loss of productivity and financial loss. This study examines the vulnerabilities and risks associated with computer numerical control machines, in particular, systems utilizing the LBP16 protocol for controller-machine communications. The study reveals that an adversary can execute cyber-physical attacks such as sabotage and denial of service. The potential security threats emphasize the importance of implementing robust security measures to mitigate the cyber risks to computer numerical control machines.

关键词： Subtractive Manufacturing Computer Numerical control Machine Cyber-Physical Attacks Sabotage Denial of Service

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