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IEEE 26th International conference on Intelligent Transportation systems (ITSC)

作者： Daman, Alexander Liu, Xiaoyu Dabiri, Azita De Schutter, Bart Delft Univ Technol Delft Ctr Syst & Control NL-2628 CD Delft Netherlands

ISBN: (纸本)9798350399462

Timetables determine the service quality for passengers and the energy consumption of trains in metro systems. In metro networks, a timetable can be made by designing train departure frequencies for different periods of the day, which is typically formulated as a mixed-integer linear programming (MILP) problem. In this paper, we first apply Benders decomposition to optimize the departure frequencies considering time-varying passenger origin-destination demands in metro networks. An epsilon-optimal Benders decomposition approach is subsequently used to reduce the solution time further. The performance of both methods is illustrated in a simulation-based case study using a grid metro network. The results show that both the classical Benders decomposition approach and the epsilon-optimal Benders decomposition approach can significantly reduce the computation time for the optimization of train departure frequencies in metro networks. In addition, the epsilon-optimal Benders decomposition approach can further reduce the solution time compared to the classical Benders decomposition approach when the problem scale increases while maintaining an acceptable level of performance.

关键词： Energy utilization

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Design of IOT Based Self Powered Smart WQMS using Filter Optimization with Efficient Sensor Node 2

Design of IOT Based Self Powered Smart WQMS using Filter Opt...

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2nd IEEE International conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Singh, Joginder Srivastava, Alok Dalal, Vipin Mvn University HR Faridabad India University of Delhi Fms Delhi India

ISBN: (纸本)9798350369960

Growing population, industries, and global warming are degrading water quality, producing various diseases and health issues. The existing wireless sensor network (WSN) and internet of things (IOT) based systems to monitor water quality are not extensively explored and are deficient in filter optimization (FO) and efficient sensor node. In this research, a self-powered system (SPS) is proposed to monitor contamination of water in real-time. The proposed method comprises smart sensors array measuring potential of hydrogen (pH), electrical conductivity (EC), pressure, flow rate, water recovery ratio (WRR), and Total Dissolved Solid (TDS) before and after filtration through the membrane. The measured physical parameters are also collected and displayed through Arduino Pro Mini microcontroller at both ends. The data accumulated at both ends are transmitted to a master node and then to an open source cloud server named ADDA Fruit IO through ESP32 WSN modules for remote monitoring. Twelve highly saline random water samples are collected periodically to analyze the proposed system performance. The above physical parameters are analyzed using statistical methods such as multiple regression, analysis of variance (ANOVA), and correlation. © 2023 IEEE.

关键词： ESP32 internet of things Sensor node Water quality monitoring Wireless sensor network

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Bilevel access control and constraint-aware response provisioning in edge-enabled software defined network-internet of things network using the safeguard authentication dynamic access control model

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INTERNATIONAL JOURNAL OF COMMUNICATION systems 2024年第18期37卷

作者： Sahana, D. S. Brahmananda, S. H. GITAM Univ GITAM Sch Technol Dept CSE Bengaluru Karnataka India Ashtaksha Labs Pvt Ltd Bengaluru Karnataka India

By controlling the network, the internet of Things (IoT)-connected software-defined network (SDN) limits the scalability of IoT devices. Since SDN depends on a centralized controller that attackers can easily affect, it is incredibly susceptible to attacks. Secure access control to the SDN controller was the focus of the prior methods for controller scalability and restricted trust management. A framework called Safeguard Authentication Dynamic Access control (SANDMAC) is suggested to safeguard and offer useful services to enterprises. Authentication confirms legitimacy after all users and applications have been registered. To improve network security, policies let users grant access to account attributes, legal activities, and temporal components. The administrator lessens conflicts between the methods by validating and saving the policies in the database. The services are provided to dependable customers using the forensic-based investigation algorithm, depending on the quality of service and software level agreements requirements, decreasing reaction times and maximizing resource usage. performance comparisons between the new and previous efforts are validated using a variety of parameters, and the proposed work is validated using the iFogSim application. According to the findings, SANDMAC significantly raises key performance indicators. SANDMAC specifically keeps false positives at 3.5% and accomplishes a low response time of 60 ms for roughly 800 authorized accesses. SANDMAC is a better option because of these enhancements, which result in longer network lifetimes and more dependable data transmission.

关键词： access control forensic based investigation (FBI) internet of Things service provisioning software-defined networks

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A Novel Wi-Fi Mesh network Framework for Efficient Mobile Data Transmission 10

A Novel Wi-Fi Mesh Network Framework for Efficient Mobile Da...

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10th International conference on internet of Things, Big Data and Security, IoTBDS 2025

作者： Ou, Yu-Jie Chen, Yan-Ming Yeh, Chun-Chao Department of Computer Science and Engineering National Taiwan Ocean University Keelung202301 Taiwan

ISBN: (纸本)9789897587504

The current trend involves the use of robots and various IoT devices to assist in production and development. In the future, with the integration of AI technology, related applications will become even more widespread. Within this context, whether it is command transmission, equipment status reporting, or equipment condition monitoring, a stable network environment is essential. Presently, the technology can be mainly categorized into wired networks, wireless networks (Wi-Fi), and mobile networks. While wired networks are fast and stable, they are constrained by physical lines and cannot be used in environments requiring interlaced movement. Wireless networks face disconnection issues when crossing different APs. While mobile networks, particularly those using 5G, offer excellent real-time performance, the establishment of private networks is expensive and the signal sources are relatively singular. This study proposes the use of Wi-Fi technology combined with the UDP (User Datagram Protocol) and QUIC (Quick UDP internet Connections) protocols to create a new type of multipath network system. This system aims to reduce the adverse effects of physical environmental changes and wireless access point (AP) device transitions, achieving a low-cost, high-speed, highly mobile, and secure network environment in specific settings. The proposed scheme leverages the encryption and security features of the QUIC protocol to protect data privacy while supporting the needs of high-mobility applications. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Wireless mesh networks (WMN)

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TurboBurst: A High Dimensional Data Classification approach for identifying Bursty Links in a Highly Spatiotemporal Correlated Sensor network 27

TurboBurst: A High Dimensional Data Classification approach ...

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27th IEEE International conference on Intelligent Engineering systems, INES 2023

作者： Muriira, Lawrence Mwenda Kenya Methodist University School of Science and Technology Nairobi Kenya

ISBN: (纸本)9798350328516

Wireless Sensor network (WSN) exhibits dynamic link behaviors. Choosing a stable route is essential for a reliable end-to-end communication. Link identification is important for utilization of both long and short terms high quality links for packet forwarding. Machine Learning has proved to learn wireless link dynamics with precision and accurately identify stable short-term link quality. This paper focuses on a data-driven design framework, turboBurst, that identifies bursty links in a highly spatiotemporal correlated Sensor network. A metric PDD is used to measure the degree of link burstiness using a Two State Markov Chain and the Earth Mover's Distance approaches as our Conditional Probability Distribution model. The model and a Kernelized Linear Support Vector Machine are exploited to identify numerous bursty links at various window sizes. The efficiency of our technique is studied over a data set obtained from an 802.15.4 network. These approaches accurately estimates between 40 and 47 short-term high quality links in the spatial temporal correlated network. Thus turboBurst shows a good performance on quality short-term link identification accuracy. © 2023 IEEE.

关键词： Wireless sensor networks

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EEOMA: End-to-end oriented management architecture for 6G-enabled drone communications

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PEER-TO-PEER networkING AND APPLICATIONS 2022年第2期15卷 1232-1254页

作者： Ali, Zainab H. Ali, Hesham A. Kafrelsheikh Univ Fac Artificial Intelligence Dept Embedded Network Syst & Technol El Geish St Kafrelsheikh 33516 Egypt Fac Engn Dept Comp Engn & Control Syst El Gomhoria St Talkha 33511 Eldakahlia Egypt Mansoura Univ Delta Univ Sci & Technol Fac Artificial Intelligence El Gomhoria St Talkha 33511 Eldakahlia Egypt

We are witnessing a new era in autonomous systems with unprecedented user experiences, excessively recovered road safety and air quality, a wide range of transportation conditions and utilization cases, as well as a plethora of advanced time-sensitive applications. To realise this ambitious vision, Vehicular Ad-hoc networks (VANET) and drones must have significantly improved communication. They must be remarkably intelligent and capable of simultaneously supporting hyper-fast, ultra-reliable, uninterrupted service, as well as low-latency massive information exchange. Although the Sixth Generation (6G) is successful in providing a seamless integration of heterogeneous elements as well as offering high coverage area with maximizing resource utilization;however, the accomplishment of faster computation, reducing bandwidth usage, low power consumption, and high throughput is remaining critical more than other purposes. This study introduces an End-To-End Oriented Management Architecture (EEOMA) based on fog computing and software-defined network (SDN) technologies for boosting the performance in hybrid networks of Vehicular Ad hoc network (VANET) and Drone. Two techniques are proposed through EEOMA to manage the data transmission on both the SDN and the drones and meet network constraints: (i) a transport service aggregation approach for simplifying the amount of traffic data traveling across the network bandwidth and (ii) a normalized throughput of a channel with adjusting the interference ratio that indicates medium access control (MAC) layer overhead. The experimental results show that there is 1.2% to 6.1% enhancement of packet delivery and packet loss ratios. More trustworthiness in performance measurement is reached by the proposed EEOMA in terms of total throughput, response time, and power consumption.

关键词： Drone networks Data transmission Cellular network Fog computing internet of things network throughput Vehicular ad hoc network Software-defined network

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Model Predictive control for Automated network Assurance in Intent-Based networking enabled Service Function Chains 36

Model Predictive Control for Automated Network Assurance in ...

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36th IEEE/IFIP network Operations and Management Symposium, NOMS 2023

作者： Avgeris, Marios Leivadeas, Aris Athanasopoulos, Nikolaos Lambadaris, Ioannis Falkner, Matthias Carleton University Department of Systems and Computer Engineering Ottawa Canada Ácole de Technologie Supérieure Department of Software and It Engineering Montreal Canada Queen's University School of Electronics Electrical Engineering and Computer Science Belfast United Kingdom Cisco Systems Ottawa Canada

ISBN: (纸本)9781665477161

Recent trends in network Function Virtualization (NFV) combined with internet of Things (IoT) and 5G applications have reshaped the network service offering. In particular, Service Function Chains (SFCs) can associate network functions with physical and virtual resources towards providing a complete network service. Concurrently, the management of a continuously expanding network and the fulfillment of the applications' requirements pave the way for autonomic network solutions. Intent Based networking (IBN) is a novel paradigm that aims to achieve the automatic orchestration of network services and the assurance of their performance. Accordingly, in this paper, we propose a novel automated network assurance model, based on Model Predictive control, to guarantee the quality of Service (QoS) and security requirements of multi-tenant and IBN-enabled SFCs. In this context, corrective decisions are proactively taken, in the form of incoming intent relocations among the SFCs. The results reveal that our model can assure with high probability the application requirements and minimize QoS violations. © 2023 IEEE.

关键词： network function virtualization

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performance Analysis of CR-NOMA Based on Untrusted Relay in IoT 6

Performance Analysis of CR-NOMA Based on Untrusted Relay in ...

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6th IEEE International conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Liang, Zanyang Li, Enyu Wang, Ye Zheng, Meijuan School of Information and Control Engineering Qingdao University of Technology Qingdao China

ISBN: (纸本)9798350399059

Cognitive radio (CR) technology can be used as a key technology for wireless communication to integrate heterogeneous networks, increasing channel capacity and improving spectrum efficiency because secondary users can access to the spectrum of the primary network for communication without authorization. It can, to some extent, pose communication security issues. To address this issue, a system model combining CR network with non-orthogonal multiple access (CR-NOMA) is proposed, in which secondary users are utilized to support the primary network communication while cognitive users are untrusted. To begin, the proposed system CR-NOMA model is constructed in the internet of Things to guarantee that it is compatible with a wider range of scenarios. Secondly, physical layer security technologies such as redundant information and jamming signal are used to improve the secrecy performance. Finally, the closed-form results for the exact and asymptotic outage probabilities of the near-end user and the remote user are studied, taking information secrecy into account. The secrecy throughput performance of various users is examined. The simulation results demonstrate that using cognitive users as relays to forward information can significantly improve the performance of the proposed system. The performance of the remote user, in particular, demonstrates that the considered model may effectively improve the quality of service of the cellular-edge user and therefore expand the coverage of the base station. © 2023 IEEE.

关键词： internet of things

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Air pollution detection and Monitoring with the smart sensor interface on the IoT platform

Air pollution detection and Monitoring with the smart sensor...

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2023 Annual International conference on Emerging Research Areas: International conference on Intelligent systems, AICERA/ICIS 2023

作者： Prajitha, C. Sridhar, K.P. Deepa, S. Baskar, S. Abubeker, K.M. Centre for Interdisciplinary Research Karpagam Academy of Higher Education Department of Electronics and Communication Engineering Coimbatore India Karpagam College of Engineering Department of Ece Coimbatore India Amal Jyothi College of Engineering Department of Electronics and Communication Engineering Kerala India

ISBN: (纸本)9798350303452

Air pollution has devastating impacts on the well-being of people, creatures, and ecosystems and the stability of the environment. The proportion of contaminants and strange circumstances in an area may be precisely monitored by an air pollution monitoring system, which has been recommended to mitigate and control air pollution. Furthermore, numerous IoT-related technologies have been created to analyze and monitor different metrics of air quality to lessen air pollution's negative effects. This internet of Things (IoT)-based approach aims to track pollution in various locations, focusing on urban areas, utilizing a network of interconnected sensors. It's proposed that different stations be located in other parts of cities. Stations update the IoT cloud with data regularly. A smart sensor is a device that can collect data from its surrounding environment and analyze it using onboard computing capabilities after detecting a particular input. This article suggests an internet of Things (IoT)-enabled smart sensor Interface (IoT-SSI) system for monitoring the air quality in densely populated places like shopping complexes. The sensors like MQ-2, MQ-4, MQ-5, MQ-6, MQ-7, MQ-8, and MQ-135, Temperature, and Humidity sensors are embedded to monitor the air quality. The platform's sensor networks use advanced processing utilizing multiple-input-single-output neural networks to get gas concentration values that account for temperature and humidity. The realtime readings from the sensor fusion model give a vast amount of data collecting and digitally providing services on these capabilities. In addition, it looks at various scenarios where IoT air quality monitoring technologies were tested and successfully passed in shopping complexes. © 2023 IEEE.

关键词： internet of things

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Triple Pseudo-Siamese network with Cross-Contextual Attention for Medical Image Retrieval 2

Triple Pseudo-Siamese Network with Cross-Contextual Attentio...

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2nd International conference on Intelligent Cyber Physical systems and internet of Things (ICoICI)

作者： Kavitha, G. Lohumi, Yogesh Kant, Kamal Bhargav, H. K. Harshal, Patil Maranan, Ramya Univ BDT Coll Engn CS&E Davangere 577004 India Graph Era Deemed Be Univ Dept Comp Sci & Engn Dehra Dun Uttarakhand India CSJM Univ Sch Engn & Technol Dept Comp Sci & Engn Kanpur 208024 UP India Shridevi Inst Engn & Technol Ind Inst Interact Cell IIIC Tumakuru 572106 Karnataka India Shridevi Inst Engn & Technol Dept Comp Sci & Engn Tumakuru 572106 Karnataka India IILM Univ Sch Comp Sci & Engn Greater Noida 201306 Uttar Pradesh India SIMATS Dept Res & Innovat Saveetha Sch Engn Chennai 602105 Tamil Nadu India

ISBN: (纸本)9798331540661;9798331540678

Hospitals are now increasingly using digital imaging data, therefore medical image archives become larger and larger. Sizable databases of these sorts are difficult to organize and query;hence there is a need for content-based medical image retrieval (CBMIR) solutions. The CBMIR systems have a main challenge which is the semantic gap among the high level semantic detail obtained by human beings and low level visual detail rendered by imaging equipments. This research presents a novel approach to medical image retrieval that uses ImageCLEFMed 2009 dataset in order to address them. By pre-processing phase, we mean an improved square root Sage-Husa adaptive Kalman filter technique used for increasing the quality of images while reducing noise. For feature extraction, it combines Short-Time Fourier Transform and Continuous Wavelet Transform (STFT-CWT) together. The Triple Pseudo-Siamese network with Cross-Contextual Attention (TPS-CCA), which captures complex patterns and relationships within the field of medicine, forms the core of this methodology. Salp Swarm Optimization has been employed for fine-tuning parameters of TPS-CCA model in order to improve its performance further. Therefore, this method shows significantly better accuracy, precision, sensitivity, specificity and F1-score compared to existing ones. This system provides a robust and efficient solution for retrieving relevant medical images, potentially aiding in improved diagnostics and patient care. The proposed method attains higher accuracy as (99.4%), precision as (99.5%), sensitivity as (99.6%), specificity as (99.8%), F1-score as (99.6%) and lower error rate as 3.

关键词： Salp Swarm Optimization Triple Pseudo-Siamese network Cross-Contextual Attention modified square root Sage-Husa adaptive Kalman filter

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