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3rd International Conference on Hot Information-Centric networking, HotICN 2020

作者： He, Wenji Yao, Haipeng Mai, Tianle Guizani, Mohsen Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China Qatar University Computer Science and Engineering Department Doha Qatar

ISBN: (纸本)9781728192161

Content distribution is the most critical task for the current Internet, (e.g., the estimated video traffic will reach 82 percent of the Internet traffic by 2022). With the fast increase of load of the network, traditional host-centric based network paradigm (i.e., TCP/IP) faces great challenges in terms of efficiency, security, and privacy. To solve the problems confronting the current Internet, the Information-Centric Network (ICN) becomes a promising solution, where the focal point is identified content rather than specific host addresses. This paradigm brings many benefits, e.g., network traffic reduction, low retrieval latency. Besides, benefiting from the advance of programmable network hardware, the operator can reconfigure the network hardware' behavior, thus providing hardware support to describe the ICN instances. However, ICN also poses new challenges to cache management. The cache redundancy and unequal resource allocation will seriously affect the performance of the network. In this paper, we propose a distributed variational Bayes aided content popularity prediction algorithm. The extensive and indepth simulations are performed to evaluate our proposed algorithm in comparison to the other state-of-the-art schemes. © 2020 IEEE.

关键词： Barium compounds

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Condition Generative Adversarial Network Deep Learning Model for Accurate Segmentation and Volumetric Measurement to Detect Mucormycosis from Lung CT Images

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Open Public Health Journal 2024年 17卷

作者： Chakrapani, Kannan Safa, M. Gururaj, H.L. Ravi, Vinayakumar Ravi, Pradeep Department of Information Technology School of Computing SASTRA Deemed University Tamil Nadu Thanjavur 613401 India Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Center for Artificial Intelligence Prince Mohammad Bin Fahd University Khobar 34754 Saudi Arabia Department of Computer Science and Engineering GSSS Institute of Engineering and Technology for Women Karnataka Mysuru India

Introduction: Mucormycosis (black fungal attack) has recently been identified as a significant threat, specifically to patients who have recovered from coronavirus infection. This fungus enters the body through the nose and first infects the lungs but can affect other body parts, such as the eye and brain, resulting in vision loss and death. Early detection through lung CT scans is crucial for reliable treatment planning and management. Methods: To combat the above problems, this paper introduces a Condition Generative Adversarial Network Deep Learning Model (CGAN-DLM) to facilitate the automatic lung CT image segmentation process, contributing to accurately identifying Mucormycosis earlier. This deep learning model employed different pre-processing strategies over raw lung CT images for extracting its ground truth values based on potential morphological operations. It adopted CGAN to segment the region of interest used for diagnosing mucormycosis with the pre-processed images and their related truth values. Results: It also included a volumetric assessment approach that significantly identified the change in lung nodule size before and after the infection of mucormycosis. Conclusion: The extensive experiments of the proposed CGAN-DLM conducted using lung CT images taken from the LIDC-IDRI database confirmed sensitivity of 98.42%, specificity of 98.86% and dice coefficient index of 97.31%, on par with the benchmarked lung CT images-based Mucormycosis detection approaches. © 2024 The Author(s). Published by Bentham Open.

关键词： Condition generative adversarial network (CGAN) Dice coeficient index Lung CT images Lung nodule volumetric assessment Mucormycosis (black fungal attack) Potential morphological operations

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Dynamic resource provisioning of a scalable E2E Network Slicing Orchestration System

arXiv

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arXiv 2022年

作者： Afolabi, Ibrahim Prados-Garzon, Jonathan Bagaa, Miloud Taleb, Tarik Ameigeiras, Pablo Department of Communications and Networking School of Electrical Engineering Aalto University Finland Department of Computer and Information Security Sejong University Seoul Korea Republic of Research Centre for Information and Communications Technologies of the University of Granada Department of Signal Theory Telematics and Communications University of Granada Granada Spain

Network slicing allows different applications and network services to be deployed on virtualized resources running on a common underlying physical infrastructure. Developing a scalable system for the orchestration of end-to-end (E2E) mobile network slices requires careful planning and very reliable algorithms. In this paper, we propose a novel E2E Network Slicing Orchestration System (NSOS) and a Dynamic Auto-Scaling Algorithm (DASA) for it. Our NSOS relies strongly on the foundation of a hierarchical architecture that incorporates dedicated entities per domain to manage every segment of the mobile network from the access, to the transport and core network part for a scalable orchestration of federated network slices. The DASA enables the NSOS to autonomously adapt its resources to changes in the demand for slice orchestration requests (SORs) while enforcing a given mean overall time taken by the NSOS to process any SOR. The proposed DASA includes both proactive and reactive resource provisioning techniques). The proposed resource dimensioning heuristic algorithm of the DASA is based on a queuing model for the NSOS, which consists of an open network of G/G/m queues. Finally, we validate the proper operation and evaluate the performance of our DASA solution for the NSOS by means of system-level simulations. © 2022, CC BY-NC-ND.

关键词： 5G mobile communication systems

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Analyzing Characteristics for Two-Step SET Operation Scheme for Improving Write Time in Nanoscale Phase-Change Memory (PCM)

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Journal of Nanomaterials 2022年第0期2022卷

作者： Mohseni, Milad Alkhayyat, Ahmed Balaji Srikaanth, P. Alrubaie, Ali Jawad Alguno, Arnold C. Capangpangan, Rey Y. Singh, Bhupesh Kumar Department of Computer Engineering Islamic Azad University Tabriz Iran Department of Computer Technical Engineering College of Technical Engineering Najaf Iraq Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Campus Chennai India Department of Medical Instrumentation Techniques Engineering Al-Mustaqbal University College Babylon Iraq Department of Physics Mindanao State University Iligan Institute of Technology Tibanga Highway Iligan City9200 Philippines Department of Physical Sciences and Mathematics College of Science and Environment Mindanao State University at Naawan Misamis Oriental Naawan9023 Philippines Arba Minch Institute of Technology Arba Minch University Ethiopia

PCM (phase-change memory) is a memory innovation that has gained prominence as a capacity-class memory for computer systems. It is made up of a tiny functional amount of phase-change material that is located in the middle of two electrodes. In PCM, data is kept by utilizing the difference in electrical resistance between a crystalline phase, which has a high resistance, and its amorphous phase, which has a low resistance. Using electrical pulses, the phase-change material would be shifted from a high to the low conductive region and conversely. However, the device's material science concerned with PCM has been generally studied, and questions remain regarding their electrical, warm, and fundamental aspects since its publication in the 1960s. One major downside of PCM is its low heat conductivity, which causes delays in the energy charging/discharging procedure and hardware efficiency. As a result of this, one of the primary focuses of PCM studies has been the improvement of PCM's heat conductivity through the utilization of nanotechnology and nanomaterials. Nanotechnology has been developing ultrasmall nanoparticles to improve traditional PCMs' thermophysical characteristics. These nanomaterials, such as metal, metal oxide, and carbon, will significantly boost PCM's thermal properties, including supercooling, viscosity, and heat capacity. An overview of PCM devices is presented in this article, which underlies perusing and composition activities. Consequently, we offered novel PCM devices and materials. Therefore, the total study is qualitative, and no machine learning approach is used. Because of this, we cannot say that the data is quantitative. Our work includes both test representations of the specific features observed in nanoscale PCM devices and material science demonstrations. In the end, we provide a point of view on some remaining open inquiries and possible future exploration directions. Copyright © 2022 Milad Mohseni et al. This is an open access article

关键词： Thermal conductivity

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Near-field communications:characteristics,technologies,and engineering

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Frontiers of Information Technology & Electronic engineering 2024年第12期25卷 1580-1626页

作者： Yajun ZHAO Linglong DAI Jianhua ZHANG Ran JI Mengnan JIAN Hao XUE Hongkang YU Yunqi SUN Yu LU Zidong WU Zhuo XU Jinke LI Haiyang MIAO Zhiqiang YUAN Pan TANG Jiayu SHEN Tierui GONG Haixia LIU Jiaqi HAN Qiang FENG Zhi CHEN Lingxiang LI Gang YANG Yong ZENG Cunhua PAN Wang LIU Kangda ZHI Weidong HU Yuanwei LIU Xidong MU Chau YUEN Mérouane DEBBAH Chongwen HUANG Long LI Ping ZHANG State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518055China ZTE Corporation Beijing 100192China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310007China Key Laboratory of High Speed Circuit Design and EMC of Ministry of Education School of Electronic EngineeringXidian UniversityXi’an 710071China Collaborative Innovation Center of Information Sensing and Understanding Xidian UniversityXi’an 710071China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of ChinaChengdu 611731China National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China School of Electrical Engineering and Computer Science Technical University of BerlinBerlin 10623Germany School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Centre for Wireless Innovation(CWI) School of ElectronicsElectrical Engineering and Computer ScienceQueen’s University BelfastBelfast BT39DTUK School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore KU 6G Research Center Khalifa University of Science and TechnologyAbu DhabiUnited Arab Emirates

Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication *** paper presents a comprehensive survey of recent advancements in near-field technology ***,we explore the near-field propagation fundamentals by detailing definitions,transmission characteristics,and performance ***,we investigate various near-field channel models—deterministic,stochastic,and electromagnetic information theory based models,and review the latest progress in near-field channel testing,highlighting practical performance and *** evolving channel models,traditional mechanisms such as channel estimation,beamtraining,and codebook design require redesign and optimization to align with near-field propagation *** then introduce innovative beam designs enabled by near-field technologies,focusing on non-diffractive beams(such as Bessel and Airy)and orbital angular momentum(OAM)beams,addressing both hardware architectures and signal processing frameworks,showcasing their revolutionary potential in near-field communication ***,we highlight progress in both engineering and standardization,covering the primary 6G spectrum allocation,enabling technologies for near-field propagation,and network deployment ***,we conclude by identifying promising future research directions for near-field technology development that could significantly impact system *** comprehensive review provides a detailed understanding of the current state and potential of near-field technologies.

关键词： 6G Near-field technology Channel model Codebook Non-diffractive beams Orbital angular momentum engineering and standardization

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computer Vision Aided mmWave Beam Alignment in V2X Communications

arXiv

引用

arXiv 2022年

作者： Xu, Weihua Gao, Feifei Tao, Xiaoming Zhang, Jianhua Alkhateeb, Ahmed Department of Automation Tsinghua University Beijing100084 China The Department of Electronic Engineering Tsinghua University Beijing100084 China The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712-1687 United States

Visual information, captured for example by cameras, can effectively reflect the sizes and locations of the environmental scattering objects, and thereby can be used to infer communications parameters like propagation directions, receiver powers, as well as the blockage status. In this paper, we propose a novel beam alignment framework that leverages images taken by cameras installed at the mobile user. Specifically, we utilize 3D object detection techniques to extract the size and location information of the dynamic vehicles around the mobile user, and design a deep neural network (DNN) to infer the optimal beam pair for transceivers without any pilot signal overhead. Moreover, to avoid performing beam alignment too frequently or too slowly, a beam coherence time (BCT) prediction method is developed based on the vision information. This can effectively improve the transmission rate compared with the beam alignment approach with the fixed BCT. Simulation results show that the proposed vision based beam alignment methods outperform the existing LIDAR and vision based solutions, and demand for much lower hardware cost and communication overhead. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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Retraction Note: Precision agriculture: crop yields classification techniques in thermo humidity sensors

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Optical and Quantum Electronics 2024年第11期56卷 1-1页

作者： Sakthipriya, S. Naresh, R. Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India Department of Networking and Communications SRM Institute of Science and Technology Chennai India

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RETRACTED ARTICLE: Performance Analysis of Malicious and Link Failure Detection System Using Deep Learning Methodology

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Wireless Personal Communications 2021年第1期127卷 25-26页

作者： Kalaiselvi, K. Vanitha, L. Deepa Thilak, K. Rajesh Kumar, T. Saranya, S. Kumaresan, K. Department of Networking and Communications School of Computing SRM Institute of Science & Technology (SRMIST) Kattankulathur India Department of Electronics and Communication Engineering Prathyusha Engineering College Thiruvallur India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Electronics and Communication Engineering Easwari Engineering College Ramapuram Chennai India Department of Computer Science and Engineering K.S.R. College of Engineering Tiruchengode India

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Optimizing Minimum Spanning Tree Algorithm for Efficient Graph Processing in Big Data

Optimizing Minimum Spanning Tree Algorithm for Efficient Gra...

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Innovations in Communications, Electrical and computer engineering (ICICEC), International Conference on

作者： S. Rani R. Roseline N. Mohankumar A. Clementking A. Arokiaraj Jovith S. Sujatha Department of BCA/IT Vels Institute of Science Technology & Advanced Studies (VISTAS) Chennai Tamil Nadu India PG Department of Computer Applications St. Joseph’s College of Arts and Science (Autonomous) Cuddalore Tamil Nadu India Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune Maharastra India Mount Carmel College (Autonomous) Bengaluru Karnataka India Department of Networking and Communications College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376524

Optimizing Minimum Spanning Tree (MST) techniques improve large data graph processing. Developing improved methods to manage large-scale data set computational complexity is the goal. To calculate MSTs in large networks faster and cheaper, better data structures and parallel processing are used. This entails improving algorithms and creating new ones for scalability and accuracy. The goal is to design a robust system that can handle enormous graphs quickly and reliably, improving big data analysis and decision-making. The focus is on algorithmic efficiency, resource optimization, and real-world big data application. Protein Structure Dataset shows the Runtime Efficiency of Optimized MST Algorithm in data processing with up to 1,000,000 data nodes, with Initial Runtime (seconds) values of 300-1600 and Optimized Runtime (seconds) values of 180-700. Memory Consumption Comparison shows the same dataset. In another instance of the same dataset from Enhanced Edge Processing, edge density ranges from 1 to 10 million, Traditional Speed (edges/second) from 5000-10000, and Optimized Speed from 10000-20000.

关键词： Proteins Runtime Machine learning algorithms Accuracy Memory management Clustering algorithms Parallel processing Data structures Data processing Computational complexity

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QoS-Aware Joint Massive Random Access Control and Resource Allocation With Colliding Preamble Reuse for Prioritized IoT

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IEEE Transactions on Vehicular Technology 2025年

作者： Guo, Ziming Zhu, Xu Wei, Zhongxiang Cao, Jie Jiang, Yufei Lau, Vincent K.N. Sun, Sumei Harbin Institute of Technology School of Information Science and Technology Shenzhen518055 China Shenzhen Municipal Key Laboratory of AIoT Communication Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Shenzhen518055 China TongJi University College of Electronic and Information Engineering Shanghai Institute of Intelligent Science and Technology China Southeast University National Mobile Communications Research Laboratory Nanjing China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering 999077 Hong Kong Institute for Infocomm Research Agency for Science 138632 Singapore

Enabling the current Internet-of-Things (IoT) and the future Internet-of-Everything (IoE) paradigms in the existing networks is challenging due to the low access efficiency amidst massive random access (RA) requests and heterogeneous applications. To address this, we investigate a novel prioritized RA control technique for massive IoT networks that cooperatively identifies adaptive access class barring (ACB) factors and preamble allocations, taking into account IoT devices' heterogeneity and limited RA resources. We derived the closed-form expression for the preamble utilization ratio (PAUR), incorporating the reusable colliding preambles and the early-stage collision detection (es-CD) technique. Two priority-guided RA request transition models are established, precisely translating RA priorities into a flexible backoff window size. Our Markov-Chain-based analytical model enables a comprehensive RA performance evaluation, demonstrating the superior performance of the proposed QoS-Aware Joint Access Control and Resource Allocation (QA-JACRA) in terms of PAUR, access delay, and throughput. This is achieved at a lower computational complexity compared to existing RA control schemes, providing a promising design approach for the activation of massive IoT devices. © 2025 IEEE.

关键词： Markov chains

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