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2022 International Conference on Electrical, computer, communications and Mechatronics Engineering, ICECCME 2022

作者： Gudepu, Venkateswarlu Pappu, Bhavani Javvadi, Tejasri Bassoli, Riccardo Fitzek, Frank H.P. Valcarenghi, Luca Devi, D.V.N. Kondepu, Koteswararao IIT Dharwad Department of Computer Science and Engineering Dharwad India RGUKT-Srikakulam Department of Computer Science and Engineering Srikakulam India RGUKT-Srikakulam Department of Electronics Communication Engineering Srikakulam India Technische Universitat Dresden Deutsche Telekom of Communication Networks Dresden Germany Telecommunications. Computer Engineering and Photonics Institute Scuola Superiore sant'Anna Pisa Italy RGUKT Nuzvid Department of Computer Science and Engineering Nuzvid India

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

5G standardization is going to reach its end, so research on 6G has started, driven by the scientific and industrial communities. 5G and especially 6G, are going to provide resources to enhance every aspect of human life via communication networks and computing. Among the different verticals, emergency services are one of the most important parts of making smart cities of the future a reality. In this context, firefighting is highly important for security and safety. However, firefighting requires ultra-reliable and low-latency communications since firefighters can be provided with advanced guidance during fire control with the employment of distributed sensors, robots, etc. Also, the use of machine learning algorithms is important for firefighters to analyze and make decisions based on the audiovisual and possibly tactile information they collect. Such a scenario cannot leverage the current cloud computing paradigm, which has significant latency issues. That is why it is important to study and design edge computing paradigms to address the goals of these scenarios and use cases since they can be capable of fulfilling latency and reliability requirements. In this situation, this work looks into how computing at Edge Micro Data Centers (EMDC) can be used to improve how fires are predicted and managed. We propose a novel three-stage architecture. The initial stage focuses on prediction and classification of the fire occurrence based on available sensor data at the EMDC, whereas the second stage deals with the fire occurrence confirmation using a convolutional neural network (CNN) classification model. After the fire occurrence has been confirmed, the final stage notifies the tenants and streams 360-degree monitoring video to the nearby fire station after processing at EMDC. The results showed that the proposed architecture can realize firefighting services with low latency. to the best of the authors' knowledge, this is the first work studying and experimentally evalu

关键词： Network architecture

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⁠Marine Ecosystem Monitoring Based on Remote Sensing Using Underwater Image Analysis for Biodiversity Conservation Model

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Remote Sensing in Earth Systems sciences 2024年第4期7卷 309-318页

作者： Rao, Chandana Narasimha Rao, A. Venkateswara Shanmugasundar, G. Hamid, Junainah Abd Haldorai, Anandakumar Naidu, G. Rama Sapthami, I. Department of Chemistry Koneru Lakshmaiah Education Foundation Green Fields Vaddeswaram Andhra Pradesh Guntur 522302 India Department of Mechanical Engineering Sri Sairam Institute of Technology Chennai 600044 India Management and Science University Selangor Shah Alam Malaysia Center for Future Networks and Digital Twin Department of Computer Science and Engineering Sri Eshwar College of Engineering Tamil Nadu Coimbatore 641202 India Department of Electronics & amp Communication Engineering Aditya University Surampalem India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

The growing focus on underwater observation and use of marine resources in recent years has led to an active research area in underwater image processing and analysis. Because of its importance in marine engineering as well as aquatic robotics, underwater picture enhancement serves as a preprocessing step to increase performance of high-level vision tasks like underwater object detection as well as recognition. While a number of studies demonstrate that underwater image enhancement methods (synthetic underwater environment image) increase the detectors’ F-measure, no research has examined the connection between these two jobs. This research proposed novel technique in remote sensing–based underwater image analysis in ecosystem monitoring in biodiversity conservation model using machine learning techniques. Here, the underwater-based remote sensing image based on marine ecosystem has been collected and analysed for noise removal with normalisation. The processed image feature extracted and classified using Gaussian spatial gradient neural network (GSGNN) and multilayer pyramid Bayes network (MPBN). The output images show coral surface texture. The experimental analysis has been carried out for various underwater dataset in terms of kappa coefficient, classification accuracy, random precision, F-measure, and normalised square error. Proposed technique kappa coefficient is 94%, classification accuracy is 98%, random precision is 95%, F-measure is 93%, and Normalised square error is 63%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Biodiversity conservation model Ecosystem monitoring Machine learning Remote sensing Underwater image analysis

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Wavelength-division-multiplexed Transmission and Dispersion Compensation Enabled by Soliton Microcombs and Cascaded Microrings

Wavelength-division-multiplexed Transmission and Dispersion ...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Liu, Yuanbin Zhang, Hongyi Liu, Jiacheng Lu, Liangjun Du, Jiangbing Li, Yu He, Zuyuan Chen, Jianping Zhou, Linjie Poon, Andrew W. State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China Photonic Device Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

We demonstrate wavelength-division-multiplexed data transmission and dispersion compensation of 25 Gb/s × 9 on-off-keying signals over a 20-km singlemode fiber using an integrated single-soliton microcomb and a cascaded microring resonator-based reconfigurable dispersion compensator. © Optica Publishing Group 2024

关键词： Dispersion compensation

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Wavelength-division-multiplexed Transmission and Dispersion Compensation Enabled by Soliton Microcombs and Cascaded Microrings

Wavelength-division-multiplexed Transmission and Dispersion ...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Optical fibers

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LoRaWAN and Biosensor-Assisted Smart City Framework to Mitigate the Effects of Lung Diseases

LoRaWAN and Biosensor-Assisted Smart City Framework to Mitig...

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2024 IEEE International Conference on Modeling, Simulation and Intelligent Computing, MoSICom 2024

作者： Abubeker, K.M. Roberts, Michaelraj Kingston Prajitha, C. Rinesh, S. Shafeena Karim, A. Jeevanandham, S. Department of Electronics and Communication Engineering Kerala India Sri Eshwar College of Engineering Centre for Advances in Signal Processing and Wireless Sensor Networks Department of Electronics and Communication Engineering Coimbatore India Karpagam Academy of Higher Education Centre for Interdisciplinary Research Department of Electronics and Communication Engineering Coimbatore India V.S.B College of Engineering Technical Campus Department of Computer Science and Engineering Coimbatore India Sri Ramakrishna Engineering College Department of Information Technology Coimbatore India

ISBN: (纸本)9798331533311

Urbanization and industrialization in cities present substantial obstacles to air quality, resulting in detrimental effects on public health, including respiratory health. This research introduces an Internet of Things (IoT) framework for a smart city environment using LoRaWAN and sensor networks. The framework utilizes the ESP32 LoRaWAN module to provide real-time monitoring of essential air quality metrics, such as carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, and humidity. Integrating biosensors enhances accuracy by identifying distinct biological indicators linked to respiratory well-being. The proposed work aims to use the framework in an urban setting within a global context, demonstrating its capacity to reduce the effects of lung disorders. The ESP32 LoRaWAN module enables effective communication within the sensor network up to 20 kilometers, guaranteeing a robust and adaptable solution for smart city applications. The developed framework provides a scalable and novel method for developing healthier and more sustainable cities, decreasing respiratory disorders as urban settings develop. © 2024 IEEE.

关键词： Lung cancer

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Game-Theoretic Approach for Integrated Sensing and Computation Offloading in Vehicular Edge networks: A Utility Maximization Design

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IEEE Internet of Things Journal 2025年

作者： Wang, Lina Wu, Weihong Dai, Minghui Zh, Haijun University of Science and Technology Beijing department of Communication Engineering China Donghua University School of Computer Science and Technology Shanghai China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing China

In recent years, with the rapid development of the Internet of Vehicles (IoVs) and the widespread application of integrated sensing and communication (ISAC) in the IoVs, the integrated sensing and computation offloading in vehicular edge networks has attracted widespread attention from academia and industry. Due to the generation of a large number of latencysensitive tasks from vehicles’ real-time sensing of road conditions, coupled with the rise of other computing-intensive vehicle applications, the current computing capabilities of the onboard devices cannot meet the diverse demands of vehicular users. Therefore, it is necessary to combine the computing resources around the vehicle to complete computing tasks. With the goal of maximizing the difference between gain and consumption, this paper studies the integrated sensing and computation offloading involving roadside units (RSUs) and vehicle platoon in vehicular edge networks. Specifically, we first consider that mobile vehicles can simultaneously offload computing tasks to RSU and vehicle platoon via non-orthogonal multiple access (NOMA) technology, and construct a multi-objective optimization problem with the goal of maximizing the utility of the three parties. Then, we construct a game model among ISAC vehicle, RSU, and vehicle platoon based on the Stackelberg game. By seeking the equilibrium of the game, the optimal offloading and pricing strategy are derived, while the utility of the three parties is maximized. Finally, the simulation results show that the proposed scheme is superior to other traditional schemes, and each party in the game obtains its optimal strategy. © 2014 IEEE.

关键词： Multiobjective optimization

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UAV Trajectory Optimization Considering User Pattern and communication Coverage Fairness

UAV Trajectory Optimization Considering User Pattern and Com...

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2022 International Symposium on networks, computers and communications, ISNCC 2022

作者： Zhang, Jianfang Liu, Yaxi Huangfu, Wei University of Science and Technology Beijing Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services School of Computer & Communication Engineering Beijing China Shunde Graduate School of University of Science and Technology Beijing Guangdong China

ISBN: (数字)9781665485449

ISBN: (纸本)9781665485449

Optimizing the trajectory of Unmanned Aerial Vehicle (UAV) Base Station (BS) is an important operational task to improve the Quality of Service (QoS) for remote areas. However, existing works mainly neglect the fair coverage and dynamic Ground Users (GUs). In this paper, we propose a novel coverage fairness index (CFI) to measure whether dynamic GUs are served as fairly as possible. Then, we formulate the problem as a constrained problem with the objective of maximizing fair coverage and minimizing energy consumption while satisfying the bound constraints. An accurate and efficient Soft-Actor-Critic (SAC)-based UAV trajectory optimization algorithm is proposed to solve the complex constrained problem based on deep reinforcement learning. Experiments are executed to prove the feasibility and efficiency of the proposed algorithm. The results manifest that the performance of the proposed algorithm is better than that of the two existing baseline methods. © 2022 IEEE.

关键词： Energy utilization

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Surface Sampling, Vertex Manipulation and Surface Generation Based on WebGL Technologies 7

Surface Sampling, Vertex Manipulation and Surface Generation...

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7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Runchevski, Danail Rechkoska-Shikoska, Ustijana Salkoski, Rasim University for Information Science and Technology 'St. Paul the Apostle' Faculty of Communication Networks and Security Resen Macedonia University for Information Science and Technology 'St. Paul the Apostle' Faculty of Computer Science and Engineering Ohrid Macedonia University for Information Science and Technology 'St. Paul the Apostle' Faculty of Information Systems Visualisation Multimedia and Animation Ohrid Macedonia

ISBN: (纸本)9798350342154

Surface sampling is a powerful technique used in computer graphics and visualization to gather data from 3D surfaces. Surface sampling is a process of collecting visual and tactile information from real world surfaces to serve as references for artistic creations. It allows artists to study and analyze the intricate details of surfaces, such as the roughness of tree bark, the smoothness of a pebble, or the subtle variations in fabric patterns. By examining surfaces up close, artists gain insights into the nuances that make each surface visually and texturally distinct. The solution we've developed operates seamlessly on both desktop and mobile devices, utilizing the functionalities of widely used web browsers. It eliminates the need for any software installations. Our achievement is founded on fully open-source solutions, allowing users to explore 3D models without any barriers. © 2023 IEEE.

关键词： Web browsers

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On the Optimization of Flow Tables of SDN-enabled Switches 5

On the Optimization of Flow Tables of SDN-enabled Switches

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5th International Conference on communication and Information Systems, ICCIS 2021

作者： Chen, Lishui Zhang, Yongqi Tang, Yazhe Science and Technology on Communication Networks Laboratory Shijiazhuang China Xi'An Jiaotong University School of Computer Science and Technology Xi'an China

ISBN: (纸本)9781665422161

In SDN network, the fine grained flow matching mechanism makes number of flow entries extremely huge so that flow tables have become the bottleneck of large-scale deployment of SDN. To solve this problem, one of the known solutions is to make a hybrid flow table structure that utilizes both TCAM and other memory, such as SRAM. The motivation is to store flow entries with many wildcards or frequently used in TCAM and to store other flow entries especially those need fine grained matching in other memory to get a cheaper, high capacity flow table with acceptable matching speed. This paper follows the hybrid flow table architecture and focuses mainly on how to make high capacity and accepted matching speed flow tables. We use a Bloom Filter pipeline to store flow entries, design and implement an intermediate adaptation layer between controllers and Openflow switches to transform the corresponding messages. The experiments results show that the flow table space can be effectively reduced to 33 bits for one flow entry, and the packet matching time can be substantially reduced compared with CPqD software switch. © 2021 IEEE.

关键词： Software defined networking

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CIL4EMTD: A Novel Class Incremental Learning Method for Encrypted Malware Traffic Detection

CIL4EMTD: A Novel Class Incremental Learning Method for Encr...

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IEEE International Conference on Data science in Cyberspace (DSC)

作者： Jiarui Li Lei Du Yilu Chen Liyi Zeng Hao Li Zhaoquan Gu School of Computer Science and Technology Harbin Institute of Technology (Shenzhen) Shenzhen China Department of New Networks Pengcheng Laboratory Shenzhen China National Key Laboratory of Advanced Communication Networks Shijiazhuang China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

With the widespread adoption of traffic encryption technologies, detecting attack behaviors in encrypted malware traffic has become a critical and challenging problem. The encrypted malware traffic contains a lot of redundant information and noise, which necessitates additional computational resources. In addition, new attack categories continue to emerge over time, resulting in traditional detection methods losing effectiveness in identifying these new attacks. To handle the above challenge, in this paper, we propose CIL4EMTD, a novel Class Incremental Learning method targeted for Encrypted Malware Traffic Detection. Our method leverages clustering techniques to enrich the extraction of dataset features, while specifically customizing LwF for detecting encrypted malware to optimize the stability of model training via efficient knowledge distillation. To verify the effectiveness of CIL4EMTD, we conduct experiments comparing it with other class incremental learning methods. The experiment results show that CIL4EMTD demonstrates state-of-the-art performance on a real-world dataset, achieving a recognition accuracy of 94.34% for new categories while maintaining the average accuracy for known categories within a margin of less than a 10% decline.

关键词： Training Incremental learning Accuracy Machine learning algorithms Noise Network security Feature extraction Malware Stability analysis Cryptography

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