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34th Irish Signals and systems conference (ISSC)

作者： O'Brien, William Hayes, Martin Penica, Mihai McCann, Jeff Moore, Denis O'Connell, Eoin Univ Limerick Dept Elect & Comp Engn Limerick Ireland

ISBN: (纸本)9798350340570

High performance networking is at the core of every industrial system, as more and more companies look inwards towards the digital transformation of their entire manufacturing environment. The driving factor for all these changes is Industry 4.0, there are many options for communication systems for the latest generations of hardware with one of the most promising technologies being private 5G networks. A smart automation use case will be implemented using private 5G as the communication backbone, the performance of this communication type will be compared to other communication types that were historically used within smart automation and manufacturing settings. performance metrics will be compared to show typical performance that may be expected when deploying a private 5G communication network. The paper will also explore the roadmap for future 5G performance increases through updates and network optimization.

关键词： 5G Private 5G Smart Manufacturing Automation Industry 4.0 Robotic control Spectrum internet of Things

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Sensing the Future: Challenges and Trends in IoT Sensor Technology 4

Sensing the Future: Challenges and Trends in IoT Sensor Tech...

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4th International conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Rajora, Ricky Rajora, Aarju Sharma, Bhanu Aggarwal, Priyanshi Thapliyal, Siddhant Chitkara University Institute of Engineering and Technology Chitkara University Punjab 140401 India Chandigarh Engineering College Department of Computer Science & Engineering Mohali India Computer Science & Engineering Graphic Era Hill University Uttarakhand Dehradun248002 India Computer Science & Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350307757

In the ever-evolving world of the internet of Things (IoT), sensors play a crucial role as essential parts, linking and merging different elements to create a smart worldwide network. This study examines the crucial function of sensors in the internet of Things (IoT) ecosystem, where they serve as sensory organs that translate the intricacies of the physical world into a uniform language for networked systems. The main emphasis is on their ability to gather and evaluate factual data from the surroundings, which impacts the performance and effectiveness of IoT applications in many industries. This research explores the uses and relevance of many sensor types, including temperature, humidity, proximity, motion, gas, biometric, vibration, image, infrared (IR), occupancy, water quality, pressure, light, and sound sensors. Although sensors contribute to the improvement of automation, control systems, and predictive analysis, they also give rise to issues in terms of security, interoperability, and power efficiency. The convergence of edge computing, artificial intelligence (AI), quantum sensors, 5G connection, and improved sensor integration has the potential to bring about significant changes in the internet of Things (IoT) environment. The study provides a thorough survey of sensor applications in several domain including healthcare, agriculture, smart cities, and automotive sectors. Lastly, it examines the difficulties and potential opportunities, highlighting the vital significance of sensors in influencing the future of interconnection and data-driven decision-making. © 2024 IEEE.

关键词： internet of things

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Investigation on End-To-End Congestion control Algorithm in Multi-Hop Ad-Hoc network 9

Investigation on End-To-End Congestion Control Algorithm in ...

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9th International conference on Wireless Communications, Signal Processing and networking, WiSPNET 2024

作者： Joseph Auxilius Jude, M. Diniesh, V.C. Sneha, A. Subhika, S. Vimal Sanjeevi, S. Sri Yaalini, M. ECE Kongu Engineering College Perundurai India

ISBN: (纸本)9798350350845

A multi-hop wireless network forms a formidable solution to overcome spectrum deficit and coverage issues in wireless conditions. As wireless internet remains crucial in connecting people from remote locations, a vast chunk of web traffic relies solely on Transmission control Protocol (TCP) to deliver packets between end systems. In the paper, an initiative is made to analyze the traffic stability under a multi-hop wireless link. TCP manages congestion by adjusting the transmission window size. In this regard, two diverse end-To-end traffic or congestion control algorithms, i.e., linear and concave-based window growth patterns, are subjected to evolution in mobility, traffic, and error rate conditions. The traffic performance of the wireless network is measured with these algorithms using network Simulator-3 (NS-3). © 2024 IEEE.

关键词： Transmission control protocol

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A question-centric review on DRL-based optimization for UAV-assisted MEC sensor and IoT applications, challenges, and future directions

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VEHICULAR COMMUNICATIONS 2025年 53卷

作者： Amodu, Oluwatosin Ahmed Mahmood, Raja Azlina Raja Althumali, Huda Jarray, Chedia Adnan, Mohd Hirzi Bukar, Umar Ali Abdullah, Nor Fadzilah Nordin, Rosdiadee Zukarnain, Zuriati Ahmad Univ Putra Malaysia Dept Commun Technol & Network Upm Serdang 43400 Selangor Darul Malaysia Univ Kebangsaan Malaysia Dept Elect Elect & Syst Engn Ukm Bangi 43600 Selangor Malaysia Imam Abdulrahman Bin Faisal Univ Coll Sci & Humanities Comp Sci Dept POB 31961 Jubail Ind City Saudi Arabia Univ Gabes Natl Engn Sch Gabes MACS Res Lab Gabes 6029 Tunisia Multimedia Univ Fac Informat Sci & Technol Ctr Intelligent Cloud Comp CICC Melaka 75450 Malaysia Taraba State Univ Fac Comp & Artificial Intelligence Dept Comp Sci ATC Jalingo 660213 Nigeria Sunway Univ Sch Engn & Technol Dept Engn 5Jalan Univ Bandar Sunway 47500 Selangor Darul Malaysia

Unmanned Aerial Vehicle (UAV)-assisted internet of Things (IoT) applications vary widely including data monitoring, data collection and analysis, intelligent navigation and object tracking, surveillance and emergency response, vehicular and intelligent transport, and agricultural, marine, and photogrammetry. Mobile Edge Computing (MEC)-based UAV-assisted IoT networks enable resource-constrained mobile or IoT devices to offload computationally demanding tasks to UAVs or edge nodes with more computing power in order to improve battery consumption, performance, or quality of Service. UAV-assisted IoT applications generally require a lot of precision for efficient UAV control involving UAV movement and position optimization and Deep Reinforcement Learning (DRL) has recently been identified as one of the most prominent techniques for facilitating this and optimizing of the terrestrial network performance, thus improving the operation of these applications. This paper aims to answer twelve important research questions relating to the research on DRL for Mobile Edge Computing (MEC)-based UAV-assisted sensor and IoT applications from 47 systematically selected articles. The questions cover a variety of topics including the UAV-assisted MEC IoT applications studied, variants of deployed DRL, the purpose of DRL, Markov Decision Processes (MDPs) components, unique network architectural features, environments and integrated technologies, role of UAVs, optimization constraints, joint optimization frameworks, energy-management techniques, metrics examined, benchmark algorithms and performance results as well as identified probable future considerations based on the review. Lastly, the challenges and future directions of DRL application in UAV-assisted MEC systems are discussed. This paper aims to provide both communication generalists and optimization specialists with a comprehensive understanding of the research landscape in this field.

关键词： Architecture Deep Reinforcement Learning Computation offloading Task offloading Metrics Multi-Access Edge Computing Mobile Edge Computing Unmanned Aerial Vehicles Drones internet of Things Wireless sensor networks

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A Stochastic network Calculus Model for TSCH Schedulers 29

A Stochastic Network Calculus Model for TSCH Schedulers

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29th IEEE Symposium on Computers and Communications (IEEE ISCC)

作者： Rabet, Iliar Fotouhi, Hossein Alves, Mario Champati, Jaya Prakash Gross, James Vahabi, Maryam Bjorkman, Mats Malardalen Univ Vasteras Sweden Politecn Porto ISEP Porto Portugal IMDEA Networks Inst Madrid Spain KTH Royal Inst Technol Stockholm Sweden

ISBN: (纸本)9798350354249;9798350354232

Low-power wireless internet of Things (IoT) devices employ Time Slotted Channel Hopping (TSCH) Medium Access control to achieve predictable timing behaviour. TSCH aims at collision-free scheduling by exploiting diversity over time (slots) and frequency (channels). However, existing works on performance and worst-case analysis are based on deterministic models, which lead to rather pessimistic non-realistic results, i.e. tools for probabilistic performance analysis of TSCH schedulers are still lacking. In this context, we devised a Stochastic network Calculus model that enables to calculate end-to-end delays for specific traffic flows and (deadline) violation probability, building on Moment Generating Functions. We instantiate this SNC model and provide bounds for three widely used TSCH schedulers, namely Minimal Scheduling Function, Orchestra, and a custom collision-free scheduler, with different parameters such as radio duty-cycle, radio link quality, and traffic arrival rate. We demonstrate that our proposed model closely follows the simulation results, under different network scenarios.

关键词： internet-of-Things (IoT) wireless sensor networks 6loWPAN 6TiSCH RPL stochastic network calculus performance analysis simulation schedulers Contiki COOJA

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Application of internet of Thing (IoT) for Precision Farming 16

Application of Internet of Thing (IoT) for Precision Farming

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16th International conference on Signal-Image Technology and internet-Based systems (SITIS)

作者： Songruk, Apidat Arunrungrusmi, Somchai Tunlasakun, Khanchai Suwannakhum, Sirimonpak Mungkungline, Narong Poonthong, Wittawat Yuji, Toshifumi King Mongkuts Univ Technol Thonburi Dept Elect technol Educ Bangkok Thailand King Mongkuts Univ Technol Thonburi Fac Ind Educ & Technol Bangkok Thailand

ISBN: (纸本)9781665464956

With the increasing popularity of the internet of Things (IOT) and devices getting smarter, this research has presented an idea to reform the weather information for precision farming. In this study, the information of weather forecast was prepared for air quality control systems using the sensor of network systems to increase the quality of organic vegetable in Thailand under the condition of Thailand weather The prototype model was described by the devices of embedded systems, which is gotten from the temperature and humidity sensor. Therefore, if there is any data from the input sensor, the users are allowed to access and granted to use this system, then, the log data are transmitted by the internet to the designation website by using a Wi-Fi module (ESP8266). As a result, it can be used the machine learning algorithms for implementing of monitor controller, which is applied for analyzing and collecting data to air quality control in green house

关键词： internet of Thing Arduino smart agriculture

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Research on PID control method for predictive modeling of oil pipeline infrastructure under industrial internet of things driving

Research on PID control method for predictive modeling of oi...

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2024 International conference on Algorithms, High performance Computing, and Artificial Intelligence, AHPCAI 2024

作者： Liu, Hao Dong, Hongbing Wang, Bo Xu, Yang Cai, Zhongwei Li, Xiang China Kunming China Oil & Gas Pipeline Network Corporation Yunnan Branch 650500 China

ISBN: (纸本)9781510685840

The oil pipeline system faces numerous safety hazards and operational management challenges, such as leaks, blockages, and pressure fluctuations, which may lead to environmental pollution, economic losses, and even casualties. To address these issues, this study proposes a predictive PID control method for oil pipeline infrastructure based on cloud servers and Industrial internet of Things (IIoT) technology, coupled with advanced data analysis and control algorithms, enabling comprehensive monitoring and management of oil pipeline systems. A risk assessment and control framework based on online model fusion is developed, integrating diverse data sources and optimization model algorithms to achieve intelligent monitoring and control of pipeline systems. Additionally, PID control algorithms are employed for real-time adjustment of flow rates and pressures in the pipeline system to ensure stable operation. Experimental results demonstrate that the proposed risk assessment and control framework effectively identifies anomalies in the pipeline system, while the PID control algorithm enables real-time adjustment of flow rates and pressures, enhancing the safety and stability of the pipeline system. Comparative analysis shows that the proposed control method offers a 28.96% improvement in feedback control effectiveness and can reduce the risk rate by up to 4.2 times through the predictive modeling method. © 2024 SPIE.

关键词： Feedback control

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Reconfigurable Quantum internet Service Provider

Reconfigurable Quantum Internet Service Provider

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IEEE International conference on Communications (IEEE ICC)

作者： Yang, Zhaohui Cui, Chaohan Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA Univ Arizona JC Wyant Coll Opt Sci Tucson AZ 85721 USA

ISBN: (纸本)9781538674628

Quantum network is a research topic involving fundamental quantum information science, engineering designs, and experimental implementations. Existing research works primarily pertain to theoretical architecture designs and proof-of-concept experimental demonstrations. With the recent developments in engineering quantum systems, the realization of scalable local-area quantum networks has become viable. However, the design and implementation of a quantum network is a holistic task that is way beyond the scope of an abstract design problem. As such, a testbed on which multiple disciplines can verify the design and implementation across a full networking stack has become a necessary infrastructure for the future development of quantum networks. In this work, we demonstrate the concept of quantum internet service provider (QISP), in analogy to the conventional ISP that allows for the sharing of classical information between the network nodes. The QISP is significant for the next-generation quantum networks as it coordinates the production, management, control, and sharing of quantum information across the end-users of a quantum network. We construct a reconfigurable QISP comprising both the quantum hardware and classical control software. Building on the fiber-based quantum-network testbed of the Center for Quantum networks (CQN) at the University of Arizona (UA), we develop an integrated QISP prototype based on a Platform-as-a-Service (PaaS) architecture, whose classical control software is abstracted and modularized as an open-source QISP framework. To verify and characterize the QISP's performance, we demonstrate multi-channel entanglement distribution and routing among multiple quantum-network nodes with a time-energy entangled-photon source. We further perform field tests of concurrent services for multiple users across the quantum-network testbed. Our experiment demonstrates the robust capabilities of the QISP, laying the foundation for the design and verification

关键词： Entanglement distribution network protocol design platform-as-a-service quantum communication quantum internet service provider quantum network reconfigurable network architecture routing software-defined network

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Adaptive Impedance Reshaping Strategy Based on Three-phase LCL Grid-connected Converter 8

Adaptive Impedance Reshaping Strategy Based on Three-phase L...

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8th IEEE International conference on Energy internet, ICEI 2024

作者： Wang, Qing Yang, Zhibo Zhu, Mingxing Zhang, Huaying Zhang, Hongzhao Jiao, Yadong Zhang, Fangfang Shenzhen Power Supply Co. Ltd New Smart City High-Quality Power Supply Joint Laboratory of China Southern Power Grid Shenzhen China Anhui University School of Electrical Engineering & Automation Hefei China

ISBN: (纸本)9798331523558

This article proposes an adaptive impedance reshaping strategy based on online impedance detection to provide adaptive suppression of broadband oscillation and increase the stability of grid-connected converter systems. The converter sequence impedance model and the network impedance obtained online are used to determine whether the system is at risk of oscillation. In order to enable the system to operate steadily under a variety of network conditions, the controller parameters are adaptively changed in response to the network impedance if there is a risk of oscillation. Lastly, simulation is used to confirm the efficacy of the suggested impedance reshaping strategy. The simulation findings demonstrate that the suggested approach can enhance system stability by modifying the system's phase margin in accordance with the grid impedance. Finally, an actual engineering example is used to implement the impedance reshaping technique. The findings demonstrate that the suggested approach is capable of modifying the converter control parameters in accordance with the grid impedance, thereby enhancing the system's phase margin and stability. © 2024 IEEE.

关键词： Adaptive control systems

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Big Data Analysis and Mining of Key Indicators in the Internal control System of Power Companies 3rd

Big Data Analysis and Mining of Key Indicators in the Intern...

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3rd World conference on Intelligent and 3D Technologies, WCI3DT 2024

作者： Sun, Zhibin Chen, Yunsheng Li, Zhanying Jia, Lixia Gu, Baoquan Fan, Jingjing Wu, Xiaote Ultra High Voltage Transmission Company of China Southern Power Grid Co. Ltd. Guangzhou510000 China

ISBN: (纸本)9789819791231

Products, supplies, services, etc., of the power enterprise—an essential energy industry—are intrinsically linked to the production, operation, and long-term growth of every business, government agency, agricultural sector, service sector, and more. Clean energy, dependable energy, high-quality services, and energy conservation and emission reduction have all been elevated in recent years due to the ongoing power business reform and the development of industry regulatory rules. The internal control of power firms has been subject to increased pressures due to all of these factors. In this setting, it is crucial to analyze and mine huge data for vital indications of power firms’ internal control systems. This article presents the architecture of a machine learning-based neural network that can assess the quality of power firms’ internal controls. An enhancement to the DenseNet-based network is introduced in this article, which streamlines the network's structure and parameters while simultaneously enhancing the model's performance and the rate of convergence. Thirdly, to increase feature extraction's discriminative capabilities, the network implements an enhanced attention strategy. In the end, this essay uses the suggested network to assess the quality of power firms’ internal controls. This study presents experimental evidence that the suggested strategy for assessing the quality of power firms’ internal controls is effective. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Big data analysis Internal control system Machine learning Neural network

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