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

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Real-Time Implementation Of A Static Compensator (STATCOM)/Active Power Filter For Power quality Improvement Based On Improved VF-DPC control Strategy 8

Real-Time Implementation Of A Static Compensator (STATCOM)/A...

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8th International conference on control, Decision and Information Technologies (CoDIT)

作者： Kamel, Sayahi Kadri, Ameni Faouzi, Bacha Univ Carthage Comp Lab Ind Syst INSAT Carthage Tunisia Univ Tunis Tunis Tunisia

ISBN: (纸本)9781665496070

To ensure a good quality of electrical energy at all points of the distribution network, the grid operators install several static compensators of reactive power (STATCOM) and many active power filters at some common coupling points PCC. This paper focuses on the operation of a static converter connected at PCC point performing the function of a static compensator (STATCOM) in the case of a voltage drop exceeding the standards and ensuring the function of an active power filter (APF) in the opposite case. This static converter ensures the regulation of the PCC voltage and eliminates the current harmonics produced by the non-linear loads connected to the grid. The control laws are designed to allow the converter to switch between the operation of a STATCOM and an active power filter. Furthermore, this research article represents an important aspect in scientific research concerning the control of FACT devices. A static reactive power compensator (STATCOM) for reactive power control and an active power filter (APF) performance are investigated by Improved Virtual flux based Direct Power control (IVF_DPC). The association of a static converter with the (IVF_DPC) control allows to react in a very fast time to the grid perturbations. Simulation results of an improved control scheme (IVF-DPC) for STATOM / APF are affected by MATLAB / Simulink software to demonstrate the dynamic performance of the proposed control strategy. The adopted control scheme is implemented using the dSPACE 1104 board. Real time implementation results prove the efficiency and uniqueness of the adopted strategy

关键词： Static compensator (STATCOM) Improved Virtual flux direct power control (IVF-DPC) Flexible alternative current transmission systems (FACTS) Active power filter (APF)

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Implementing QZMAC (a Decentralized Delay Optimal MAC) over 6TiSCH under the Contiki OS in an IEEE 802.15.4 network

Implementing QZMAC (a Decentralized Delay Optimal MAC) over ...

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International conference on COMmunication systems and networkS (COMSNETS)

作者： Vatsa, Shivam Vinayak Mohan, Avinash Kumar, Anurag Indian Inst Sci Bangalore Karnataka India Technion Israel Inst Technol Haifa Israel

ISBN: (纸本)9781728191270

Motivated by the emerging delay-sensitive applications of the internet of Things (IoT), there has been a resurgence of interest in developing medium access control (MAC) protocols in a time-slotted framework. The resource-constrained, ad-hoc nature of wireless networks typical of the IoT also forces the amount of control information exchanged across the network required to make scheduling decisions - to a minimum. In a previous article we proposed a protocol called QZMAC that (i) provides provably low mean delay, (ii) has distributed control(i.e., there is no central scheduler), and (iii) does not require explicit exchange of state information or control signals. In the present article, we implement and demonstrate the performance of QZMAC on a test bed consisting of CC2420 based Crossbow telosB motes, running the 6TiSCH communication stack on the Contiki operating system over the 2.4GHz ISM band. QZMAC achieves its near-optimal delay performance using a clever combination of polling and contention modes. We demonstrate the polling and the contention modes of QZMAC separately. We use an Adaptive Synchronization Technique in our implementation which we also demonstrate. Our network shows good delay performance even in the presence of heavy interference from ambient WiFi networks.

关键词： internet of Things (IoT) Medium Access control (MAC) protocols IEEE 802.15.4 6TiSCH

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Deadline-Aware Hybrid HARQ Scheme for Multi-devices Deterministic Transmission over 5G-TSN systems 15

Deadline-Aware Hybrid HARQ Scheme for Multi-devices Determin...

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15th IEEE International conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Zhao, Jian Wang, Tao Tong, Haonan He, Xinxin Yin, Changchuan Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence China

ISBN: (纸本)9798350324662

This paper studies a deadline-aware hybrid retransmission scheme for an Industrial internet of Things (IIoT) system over the 5th generation and Time-Sensitive networking (5G-TSN) system. In the considered model, multiple devices must transmit time-sensitive data flows to an edge server for real-time computing and industrial control. These scenarios require the 5G-TSN technique to realize deterministic transmission, which must complete the data transmission before the specified deadline while maintaining ultra-high reliability. Since the uncertainty of the wireless channel in 5G-TSN affects the transmission reliability, hybrid automatic repeat request (HARQ) technology is introduced to improve the transmission success probability. However, two existing mainstream HARQ negative acknowledgment-based (NACK-based) and blind schemes lead to a huge delay penalty and drain spectrum resources, respectively. These drawbacks make it challenging to meet multiple devices' diverse quality of service (QoS) requirements. To address this issue, a deadline-aware hybrid HARQ scheme that combines NACK and blind retransmission schemes is proposed to maximize the number of successfully transmitted deterministic data flows over the 5G-TSN. Specifically, we first propose the delay and reliability models for our considered 5G-TSN IIoT system. Subsequently, our proposed scheme is introduced in detail. The simulation results demonstrate that the proposed scheme can increase the number of deterministic transmission flows by 170.52% and 27.98% with 100 devices compared to 1) single NACK-based and 2) traditional hybrid HARQ schemes. © 2023 IEEE.

关键词： deterministic transmission hybrid automatic repeat request Industrial internet of Things Time-Sensitive networking

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KDDT: Knowledge Distillation-Empowered Digital Twin for Anomaly Detection 2023

KDDT: Knowledge Distillation-Empowered Digital Twin for Anom...

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31st ACM Joint Meeting of the European Software Engineering conference / Symposium on the Foundations-of-Software-Engineering (ESEC/FSE)

作者： Xu, Qinghua Ali, Shaukat Yue, Tao Nedim, Zaimovic Singh, Inderjeet Simula Res Lab Oslo Norway Univ Oslo Oslo Norway Oslo Metropolitan Univ Oslo Norway Alstom Rail Sweden AB Vasteras Sweden

ISBN: (纸本)9798400703270

Cyber-physical systems (CPSs), like train control and management systems (TCMS), are becoming ubiquitous in critical infrastructures. As safety-critical systems, ensuring their dependability during operation is crucial. Digital twins (DTs) have been increasingly studied for this purpose owing to their capability of runtime monitoring and warning, prediction and detection of anomalies, etc. However, constructing a DT for anomaly detection in TCMS necessitates sufficient training data and extracting both chronological and context features with high quality. Hence, in this paper, we propose a novel method named KDDT for TCMS anomaly detection. KDDT harnesses a language model (LM) and a long short-term memory (LSTM) network to extract contexts and chronological features, respectively. To enrich data volume, KDDT benefits from out-of-domain data with knowledge distillation (KD). We evaluated KDDT with two datasets from our industry partner Alstom and obtained the F1 scores of 0.931 and 0.915, respectively, demonstrating the effectiveness of KDDT. We also explored individual contributions of the DT model, LM, and KD to the overall performance of KDDT, via a comprehensive empirical study, and observed average F1 score improvements of 12.4%, 3%, and 6.05%, respectively.

关键词： digital twin knowledge distillation anomaly detection Train control and Management System

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Developing Frugal internet of Things From Artificial Neural network to Predict Student Mindfulness Concentration and Relaxation Levels

Developing Frugal Internet of Things From Artificial Neural ...

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Electronic Communications, internet of Things and Big Data (ICEIB), International conference on

作者： Hsiang-Yu Tsai Liang-Sian Lin Yu-Xiang Wang Yi-Ying Tsai Yi-Jie Li Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan Department of International Business Tamkang University Taipei Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

Indoor environmental quality significantly impacts student learning performance and efficiency. Studies indicate that indoor lighting highly affects student learning performance. Electroencephalography (EEG) is used to analyze the influence of correlated color temperature (CCT) on student learning performance. We developed a frugal internet of Things (IoT) system to monitor student mindfulness concentration and relaxation levels at different CCTs. The proposed IoT system includes a DHT11 sensor for detecting indoor temperature and humidity, a WS2812B sensor for CCT controlling, a galvanic skin response (GSR) sensor for measuring student stress levels, and a TGAM brainwave module measuring real-time concentration and relaxation levels. An artificial neural network (ANN) model was built using data from multiple sensors to predict student mindfulness levels.

关键词： Temperature measurement Temperature sensors Humidity measurement Artificial neural networks Electroencephalography Skin Temperature control

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performance Evaluation of the WiFi Technology Based Real-Time control Robotic Arm

Performance Evaluation of the WiFi Technology Based Real-Tim...

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2023 IEEE Colombian conference on Communications and Computing, COLCOM 2023

作者： Topon, Luis Lara-Cueva, Roman Universidad de Las Fuerzas Armadas Espe Departamento de Eléctrica Electrónica y Telecomunicaciones Sangolquí171103 Ecuador

ISBN: (纸本)9798350328400

Teleoperation in recent years has had a great technological advance. The development of remotely controlled prototypes has made it possible to carry out work where the human hand had problems. However, a limitation of these systems is the delay in data transmission and signal processing. In this context, the present degree work is based on evaluating the performance of WiFi technology in accordance with the IEEE 802.11n standard for real-time control of a robotic arm. This prototype is controlled by flex sensors that are placed on the human arm for data acquisition. The data is processed by an ESP32 controller card that sends it to another ESP32 card via WiFi signal through an MQTT server. This allows to control the robotic arm with 4 degrees of freedom. In addition, a video camera is implemented which generates the image of the process in a computer through the Node-red platform. For the evaluation of the performance of WiFi technology, an analysis of the performance metrics associated with the quality of service was carried out, these were the delay and Jitter. Testing was done with providers Celerity and CNT. The results obtained were that the average delay in a system in the absence of devices in its network is 83.38 ms and 111.56 ms, with a standard error of the delay of 8.77 ms and 21.05 ms, and a Jitter of 10, 37 ms and 22.96 ms respectively. When there are 10 devices on the network, the result is a mean delay of 142.2 ms and 231.48 ms, a standard error of the delay of 40.52 ms and 95.25 ms, and a Jitter of 45.59 ms and 107.14 ms. Therefore, it is corroborated that in the presence of greater data traffic, the delay and Jitter increase. Finally, in the distance tests when there is an absence of devices, it is shown that the delay increases directly proportional to the distance, while the Jitter increases in a minimum proportion. Thus, in 20 and 100 m the average delay is 85 ms and 503 ms with a Jitter of 9.76 ms and 10.51 ms respectively. © 2023 IEEE.

关键词： Jitter

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Optimizing HVAC System of Kuwaiti Residential Building Based on internet of Energy (IoE) Concept 8

Optimizing HVAC System of Kuwaiti Residential Building Based...

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8th International conference on Energy Research and Development, ICERD 2023

作者： Saryazdi, Sayed M.E. Baba, Younes Khan Shafaat, Ali Bahman, Ammar Architecture and Urban Planning Department Shahid Beheshti University Tehran Iran Department of Mechanical Engineering College of Engineering and Petroleum Kuwait University Kuwait

ISBN: (纸本)9781955516709

The high energy consumption of Heating, Ventilation, and Air Conditioning (HVAC) systems in Kuwaiti buildings, accounting for approximately 50% of total energy usage, has become a pressing concern in alignment with the sustainability vision of Kuwait 2035. This study aims to address this issue by proposing optimal cooling strategies that leverage the internet of Energy (IoE) concept to simultaneously reduce energy consumption and carbon emissions while ensuring occupant comfort. To achieve these objectives, a Model Predictive controller (MPC) integrated with an IoE framework is introduced as a solution for controlling the HVAC system in a residential building located in Kuwait, serving as a case study. The MPC operates as an online closed-loop feedback controller, optimizing both indoor thermal comfort and energy consumption. In order to simulate the energy performance of the building, an Artificial Neural network (ANN) model is developed and incorporated into the MPC. Leveraging the IoE paradigm, Application Programming Interfaces (APIs) are generated to acquire real-time weather conditions and electricity prices via the internet. These dynamic inputs are utilized to dynamically adjust temperature settings, further enhancing the energy efficiency of the HVAC system. The results of this study demonstrate that the MPC controller surpasses the hysteresis controller in terms of energy consumption, while still maintaining satisfactory thermal comfort levels. The integration of the IoE concept and the utilization of the ANN model in the MPC contribute to the achievement of optimal control strategies, yielding significant energy savings and a reduction in carbon emissions. © 2023 ASHRAE.

关键词： Thermal comfort

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network Traffic Prediction Using Optimized Deep Learning Techniques

Network Traffic Prediction Using Optimized Deep Learning Tec...

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Intelligent Cyber Physical systems and internet of Things (ICoICI), International conference on

作者： Pandiselvam Pandiyarajan Maheswaran Baskaran Vighnesh Bondada Jaswanth Santhosh Cherukuri Mohan Krishna Sai Muppala Sandeep Ravilla Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Kalasalingam University Krishannkoil Tamil Nadu India Department of Biotechnology Ayya Nadar Janaki Ammal College Sivakasi Tamil Nadu India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

A pervasive growth has recently been drawn to analyzing and predicting network traffic since it has applications in many diverse fields. Several tests are carried out to find immense issues around current network-based computers. Traffic Analysis in network is a recent strategy for safe, dependable, and high-quality communication through network. For evaluating network traffic, numerous techniques from those based on deep learning techniques are developed and tested. The core objective of the proposed method is to design algorithms for predicting network traffic. This proposed method is also evaluated through learning parameters. From the experimental results, it has been identified that the Recurrent Neural network works better while predicting network traffic analysis with obtained accuracies of 92.89% and 96.78%. The proposed method provides better performance as it has been compared with benchmark algorithms.

关键词： Deep learning Computers Recurrent neural networks Protocols Wireless networks Telecommunication traffic Predictive models Prediction algorithms Radio networks Forecasting

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Improving Transferability of network Intrusion Detection in a Federated Learning Setup

Improving Transferability of Network Intrusion Detection in ...

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Machine Learning for Communication and networking (ICMLCN), IEEE International conference on

作者： Shreya Ghosh Abu Shafin Mohammad Mahdee Jameel Aly El Gamal School of Electrical and Computer Engineering Purdue University USA

ISBN: (数字)9798350343199

ISBN: (纸本)9798350343205

network Intrusion Detection systems (IDS) aim to detect the presence of an intruder by analyzing network packets arriving at an internet connected device. Data-driven deep learning systems, popular due to their superior performance compared to traditional IDS, depend on availability of high quality training data for diverse intrusion classes. A way to overcome this limitation is through transferable learning, where training for one intrusion class can lead to detection of unseen intrusion classes after deployment. In this paper, we provide a detailed study on the transferability of intrusion detection. We investigate practical federated learning configurations to enhance the transferability of intrusion detection. We propose two techniques to significantly improve the transferability of a federated intrusion detection system. The code for this work can be found at https://***/ghosh64/transferability.

关键词： Deep learning Training performance evaluation Codes Federated learning network intrusion detection Training data

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Path Optimization of Complex and Large-Scale Automated Antenna Assembly Lines

Path Optimization of Complex and Large-Scale Automated Anten...

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UNIfied conference of International Workshop on Defence Applications of Multi-Agent systems, DAMAS 2023, International conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and performance Engineering network, TEPEN 2023

作者： Ma, Zeyu Wang, Hongjun Zhang, Mingliang Jiang, Fan Li, Bin School of Mechanical Electrical Engineering Beijing Information Science and Technology University Beijing100192 China Beijing International Science Cooperation Base of High-End Equipment Intelligent Perception Beijing100192 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100192 China Beijing Institute of Radio Measurement Beijing100854 China School of Information Management Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9783031494208

Considering issues such as low assembly efficiency and the inability of the assembly process index and product characteristics to be fully reflected in the traditional construction mechanical arm assembly process, the concept of a digital twin was introduced. The study involved the modeling and simulation technology of the construction mechanical arm assembly process based on the digital twin, and included some path optimization. Furthermore, according to the virtual model, a genetic algorithm was employed to optimize the path in Matlab. Additionally, the Hamiltonian cycle algorithm was utilized to enhance the efficiency of the robot and decrease the working time. Taking the assembly line of a screw arm as an example, it was demonstrated that the assembly simulation based on digital twinning can monitor the assembly process in real time. It can also optimize its configuration to improve assembly efficiency and implement an effective closed-loop feedback mechanism to enhance production efficiency, improve production quality, and reduce production cost. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Cyber Physical System

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