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

共 10552 条记录，以下是671-680 订阅

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Synthesis of an Optimal control Algorithm for a Transport Conveyor with a Reversing Section 4

Synthesis of an Optimal Control Algorithm for a Transport Co...

引用

4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Pihnastyi, Oleh Kozhevnikov, Georgii Polozhyi, Denys Dept. Internet of Things National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine Dept. Multimedia and Internet Technologies and Systems National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine Dept. Computer Systems Networks and Cybersecurity National Aerospace University «Kharkiv Aviation Institute» Kharkiv Ukraine

ISBN: (纸本)9798350395532

The analytical model of the conveyor reversing section for the synthesis of the optimal control algorithm of flow parameters of the transport system is researched. At a constant belt speed of the conveyor, the values of the flow parameters of the reversing section are determined according to the given values of the input flow. The model of the reversing section is based on the analytical PiKh-model with a constant transport delay. The relevance of developing an analytical model of the reversing section is caused by the practical need to build algorithms for optimal control of the flow parameters of a transport system with a variable structure of the transportation route. This model can be used to form a data set for training a neural network in a multi-section transport pipeline model. It is assumed that the belt speed is constant, the switching process is instantaneous, the interval between switching points is more than the transport delay. The optimal control problem of the flow parameters of the section is formulated. For the synthesis of optimal control, the Pontryagin maximum principle is used. According to the given quality criterion, the Hamiltonian of the system was written. The optimal control algorithm of the flow parameters for the transport system has been synthesized. The belt speed switching points have been defined. The proposed model can be used to design a control system with a changing structure of the transport route to decrease the specific transport costs in the mining industry. © 2023 IEEE.

关键词： Optimal control systems

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Towards a Privacy Preserving Data Flow control via Packet Header Marking 24

Towards a Privacy Preserving Data Flow Control via Packet He...

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24th IEEE International conference on High performance Computing and Communications, 8th IEEE International conference on Data Science and systems, 20th IEEE International conference on Smart City and 8th IEEE International conference on Dependability in Sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Mazumdar, Somnath Dreibholz, Thomas Copenhagen Business School Department of Digitalization Solbjerg Plads 3 Frederiksberg2000 Denmark Centre for Resilient Networks and Applications Simula Metropolitan Pilestredet 52 Oslo0167 Norway

ISBN: (纸本)9798350319934

internet infrastructure is becoming ubiquitous thanks to the advancement in computing and the network domain. Reliable network communication is essential to offer good quality services, but it is not trivial. There are privacy concerns. Metadata may leak user information, even if traffic is encrypted. Some countries have data privacy preserving-related regulations, but end-users cannot control how their data packets should travel through networks. Even worse, the user cannot declare their privacy preferences. This paper presents an approach to tackle such privacy issues through data privacy-aware routing, where users can specify their preferences for packet routing using marking and filtering. Routing can work according to such specifications. It is implemented by P4, allowing a vendor-independent realisation with standard off-the-shelf hardware and open-source software components. We presented the initial experimental results of a proof-of-concept test on a unified cloud/foe research testbed. © 2022 IEEE.

关键词： Open systems

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Optimizing Resource Allocation in Mobile Edge Computing for IIoT through Reinforcement Learning and Multiobjective Particle Swarm Optimization 2

Optimizing Resource Allocation in Mobile Edge Computing for ...

引用

2nd IEEE International conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Avv, Sudhakar Mohan, M. Maharajan, K. Habelalmateen, Mohammed I. Naga Saranya, N. SR University Department of Electrical and Electronics Engineering Telangana India Nitte Meenakshi Institute of Technology Department of ISE Bengaluru India School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil Bangalore India Universiti Tun Hussein Onn Malaysia Parit Raja Faculty of Electrical and Electronic Engineering Johor Batu Pahat Malaysia College of Technical Engineering the Islamic University Department of Computer Technical Engineering Najaf Iraq Saveetha College of Liberal Arts and Science SIMATS Department of Computer Applications Chennai India

ISBN: (纸本)9798350317558

Mobile networks are flexible enough to support a range of resource allocation models and service-based choices in computing domains, which affects both virtual reality and the Industrial internet of Things (IIOT). Virtual resource management is made easier by the Mobile Edge Computing (MEC) paradigm, which also makes edge connectivity between data terminals and execution in the core network under heavy load possible. Meeting customer requirements efficiently is achieved through thoughtful planning, aided by cognitive agents. User data, incorporating behavioral patterns, is amalgamated to cater to IIOT service types. Neural caching for memory during task execution is made easier by the use of swarm intelligence and reinforcement learning techniques. Prediction strategies optimize business operations and caching to reduce execution delays. Predictive models evaluate performance by taking into account variables like nearby user equipment and mobile edge computing resources. This method's efficacy is demonstrated by a cognitive agent model that manages resource distribution and creates networks of communication to improve service quality. For accurate resource distribution among end users, reinforcement learning techniques - more especially, Multi-Objective Particle Swarm Optimization (MOPSO) algorithms - are used. This includes building cost mapping tables and optimizing allocation in MEC. The proposed method outperforms existing algorithms like Task-Offloading and Resource Allocation Strategy and achieves a better throughput value of 785.32. © 2024 IEEE.

关键词： Communication Industrial internet of Things Mobile Edge Computing Optimization quality of Service Reinforcement Learning

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Multilevel Converter-based Dynamic Voltage Restorer for Mitigation of Voltage Disturbance in Distribution network 25

Multilevel Converter-based Dynamic Voltage Restorer for Miti...

引用

25th International Multi Topic conference, INMIC 2023

作者： Khawaja, Saad Ahmad Mahmood, Tahir University of Engineering and Technology Taxila Electrical Engineering Department Taxila Pakistan

ISBN: (纸本)9798350317701

In today's power systems, one of the main problem is power quality. The emergence of complex equipment and excessive use of power electronic devices, have made them highly dependent on the quality of the supplied power, that has increased its importance to both suppliers and consumers. Sensitive equipment's can be damaged due to voltage sag, voltage swell and harmonics present in the power system, which are mostly occurring power quality issues. This research focuses on enhancing the performance of a DVR under extreme sag and swell conditions by using a multilevel converter. In the proposed approach, we first employ the Synchronous Reference Frame (SRF) technique with positive sequence detection, followed by the integration of a Proportional-Integral (PI) controller, and lastly utilization of a Cascaded H-Bridge (CHB) five-level converter. SRF technique is employed to accurately detect and extract the fundamental components of voltage disturbances, enabling precise compensation and restoration of distorted waveforms. PI controller ensures accurate voltage regulation and robust control performance. Cascaded H-Bridge MLC topology is utilized to generate compensating voltage with increased voltage levels as compared to the conventional two-levels, reduced total harmonic distortions (THD), and improved power quality. The proposed technique is compared with traditional converter and control methods using MATLAB/Simulink simulations. The result shows significant improvements in voltage restoration, reduced THD and enhanced dynamic response under extreme sag and swell conditions. This research contributes to the advancement of power quality technologies, providing a reliable and efficient approach to voltage restoration in power distribution systems. © 2023 IEEE.

关键词： Power quality

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Analysing the Effectiveness of Intrusion Detection systems against the Mirai Botnet: A Comparative Study 15

Analysing the Effectiveness of Intrusion Detection Systems a...

引用

15th International conference on Advances in Computing, control, and Telecommunication Technologies, ACT 2024

作者： Binu, P.K. Kumar, Barun Sethia, Rishav Department of Computer Science and Application Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798331300579

The rise of the internet of Things (IoT) has led to an increased risk of cyber attacks on IoT devices, including botnet attacks. Botnets are networks of compromised devices that can be controlled remotely by cybercriminals to carry out malicious activities, such as distributed denial of service (DDoS) attacks. The Mirai botnet is one of the most notorious botnets that have caused significant damage to IoT devices worldwide. To protect IoT devices from such attacks, intrusion detection systems (IDSs) are used to detect and mitigate attacks. However, the effectiveness of IDSs against botnet attacks is still a subject of debate, as botnets are becoming more sophisticated and difficult to detect. To address this issue, this research paper aims to analyse and compare the effectiveness of three widely used IDSs, namely Snort, Zeek, and Suricata, against the Mirai botnet. The study involves simulating Mirai botnet attacks in a controlled environment and evaluating the performance of each IDS in terms of detection and mitigation capabilities. The findings of this research can help organisations to select and implement effective IDSs to mitigate the impact of botnet attacks on IoT devices. By understanding the strengths and weaknesses of different IDSs, organisations can improve the security of their IoT devices and reduce the risk of cyber attacks. Overall, this research paper contributes to the existing literature on IDSs and their effectiveness against botnet attacks, highlighting the importance of selecting and implementing effective IDSs to protect IoT devices from cyber threats. © Grenze Scientific Society, 2024.

关键词： IDS Malware Mirai network Security Snort Suricata Zeek

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A Multi-Layered Representation for Intrusion Detection System in Cyber systems Using CNN Deep Learning Algorithm

A Multi-Layered Representation for Intrusion Detection Syste...

引用

2023 International conference on Data Science and network Security, ICDSNS 2023

作者： Mehra, Ritika Sohal, Asha Shrotriya, Shikha Gupta, Varun Kumar Kalra, Nuvita Dhabliya, Ritika School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand India School of Engineering and Technology K. R. Mangalam University Department of Cse Gurugram India Invertis University Department of Law Bareilly India School of Computer Science and Applications Iimt University Meerut India Pune India Yashika Journal Publications Private Limited India

ISBN: (纸本)9798350301595

Convolutional Neural networks (CNNs), a kind of deep learning architecture, have recently shown remarkable progress in the field of computer vision. This study models network traffic as a time-series, in particular transmission control protocol/internet protocols (TCP/IP) packets in a predetermined time range, and applies supervised learning techniques to improve performance for the job of detection of intrusions (ID) in cyber security. Each experiment uses a learning rate between [0.01] and [0.05] to run the models for up to 1000 epochs. When compared to traditional machine learning classifiers, CNN and its different architectures perform very well. This is primarily because CNNs can abstractly represent low-level characteristic sets of traffic on network links in the form of high-level features. © 2023 IEEE.

关键词： network architecture

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QoE Evaluation of Real-Time Remote Operation with network Constraints in a System-of-systems 16

QoE Evaluation of Real-Time Remote Operation with Network Co...

引用

16th Annual IEEE International systems conference (SysCon)

作者： Schueler, Cedrik Gebauer, Tim Patchou, Manuel Wietfeld, Christian TU Dortmund Univ Commun Networks Inst D-44227 Dortmund Germany

ISBN: (纸本)9781665439923

With the advent of robotics, remote operation gained momentum as it allows for the control and feedback of distant systems, thus reducing human logistics and risk. Despite the growing popularity of fully autonomous systems, remote operation still retains a significant relevance due to operative requirements like manual overrides in critical situations. Such a requirement calls for a robust and reliable remote operation experience. We propose an evaluation system following a systemof-systems architecture to assist in the development of remotely operated applications with tested resilience against network effects. The system has an extensible architecture allowing the swap of real and virtual components and enables the evaluation of remote operation applications in unreliable network environments. In a proof-of-concept study, the system is implemented and used to evaluate the impact of network constraints on a teleoperated high-speed driving scenario. Our results show that the baseline setup leads to approximately equal ( +/- 0.9 %) end-to-end driver performances. Thus, other evaluations are primarily affected by additional constraints, enabling our system for extensive analyses. Comprehensive drive trials show that network latency steadily mitigates driving performance, whereas packet loss can be compensated well up to a specific value. In addition, our quality of Experience (QoE) surveys show the subjective ratings of participants exposed to network impacts.

关键词： systems architecture Packet loss quality of service Real-time systems Planning quality of experience Reliability

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SpectraNet: A Neural network for Soybean Contents Prediction 26

SpectraNet: A Neural Network for Soybean Contents Prediction

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26th International conference on Enterprise Information systems, ICEIS 2024

作者： Kobs, Henry Julio Krever, Henrique Liesenfeld Ebling, Denilson S. Trois, Celio Technology Center Federal University of Santa Maria Santa Maria Brazil Zeit Artificial Intelligence Solutions Ltd. Santa Maria Brazil Department of Physical and Inorganic Chemistry Engineering Rovira i Virgili University Tarragona Spain

ISBN: (纸本)9789897586927

Soybeans are integral to global agriculture and food production, playing a vital role in human and animal nutrition. Accurate assessment of moisture, oil, and protein contents in soybeans is crucial for various applications, including human nutrition, animal feed, and food manufacturing. This paper introduces SpectraNet, a Neural network architecture designed for predicting soybean contents using Near-infrared Spectroscopy (NIRS) data. NIRS technology provides a cost-effective and non-destructive means of analyzing agricultural samples. SpectraNet leverages a 1D convolutional Neural network and multiple prediction heads, demonstrating its efficacy in handling non-linearities present in spectral data. The architecture’s flexibility and adaptability contribute to accurate predictions, automatic feature extraction, and suitability for varying conditions. Comparative analysis with traditional Partial Least Squares Regression (PLSR) models reveals the superior performance of SpectraNet in predicting protein, moisture, and oil contents in soybeans. The presented methodology involves comprehensive data collection, laboratory analysis, and model training, showcasing the potential of SpectraNet for real-world applications in agriculture. The results highlight the efficiency and precision of SpectraNet, offering a valuable tool for advancing agricultural practices and ensuring soybean quality. Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Near infrared spectroscopy

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Optimizing the Age of Information in Mixed-Critical Wireless Communication networks

Optimizing the Age of Information in Mixed-Critical Wireless...

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IEEE International conference on Communications (IEEE ICC)

作者： Reifert, Robert-Jeron Roth, Stefan Sezgin, Aydin Ruhr Univ Bochum Inst Digital Commun Syst Bochum Germany

ISBN: (纸本)9781538674628

Beyond fifth generation wireless communication networks (B5G) are applied in many use-cases, such as industrial control systems, smart public transport, and power grids. Those applications require innovative techniques for timely transmission and increased wireless network capacities. Hence, this paper proposes optimizing the data freshness measured by the age of information (AoI) in dense internet of things (IoT) sensor-actuator networks. Given different priorities of data-streams, i.e., different sensitivities to outdated information, mixed-criticality is introduced by analyzing different functions of the age, i.e., we consider linear and exponential aging functions. An intricate non-convex optimization problem managing the physical transmission time and packet outage probability is derived. Such problem is tackled using stochastic reformulations, successive convex approximations, and fractional programming, resulting in an efficient iterative algorithm for AoI optimization. Simulation results validate the proposed scheme's performance in terms of AoI, mixed-criticality, and scalability. The proposed non-orthogonal transmission is shown to outperform an orthogonal access scheme in various deployment cases. Results emphasize the potential gains for dense B5G empowered IoT networks in minimizing the AoI.

关键词： internet of things

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Hybrid Kalman Filter-Based MPPT Design for Photovoltaic System in Energy Harvesting Optimization 2nd

Hybrid Kalman Filter-Based MPPT Design for Photovoltaic Syst...

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2nd International conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Rabeea, Waleed Ucun, Levent Yildiz Tech Univ Control & Automat Engn Dept Istanbul Turkiye

ISBN: (纸本)9783031628702;9783031628719

A novel hybrid Maximum Power Point Tracking (MPPT) strategy is introduced in this study. By integrating Kalman filter MPPT with the grey wolf optimization (GWO) algorithm, a novel hybrid MPPT method is developed. By applying this technology to the photovoltaic system to be used for energy harvesting optimization, it is possible to simultaneously enhance the system's power quality and efficiency. TheMATLAB software is utilized to simulate the proposed method, and afterward, the obtained results are subsequently compared to the most recent advancements in MPPT methods across a variety of environmental conditions. The suggested method is tested under uniform irradiance, step changing in irradiances, and the partial shading effect to showthe performance of the PVarray. Here, the irradiance and temperature data can be received via different sources and from applications such as ThingSpeak which is an example of using the means of internet of Things (IoT) in energy harvesting optimization. Furthermore, a comparison is made between the acquired outcomes and the most recent MPPT techniques, namely perturb and observe (P&O), Kalman filter (KF), and grey wolf optimization (GWO). The proposed methodology shows better efficiency, reduced power oscillation, and higher speed in comparison to conventional approaches.

关键词： Optimization MPPT Kalman Filter GWO P&O Partial Shading Photovoltaic System

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