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Top-down and bottom-up approaches to video Quality of Experience studies;overview and proposal of a new model

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arXiv 2023年

作者： Koniuch, Kamil Baraković, Sabina Husić, Jasmina Baraković De Moor, Katrien Janowski, Lucjan Wierzchoń, Michal Institute of Communication Technologies AGH University of Science and Technology Cracow Poland Faculty of Traffic and Communications University of Sarajevo Sarajevo Bosnia and Herzegovina Zmaja od Bosne bb Sarajevo71000 Bosnia and Herzegovina Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina Zmaja od Bosne bb Sarajevo71000 Bosnia and Herzegovina Department of Information Security and Communication Technology Norwegian University of Science and Technology Trondheim Norway Consciousness Lab Institute of Psychology Jagiellonian University Kraków Poland Centre for Brain Research Jagiellonian University Kraków Poland Jagiellonian Human-Centered Artificial Intelligence Laboratory Jagiellonian University Kraków Poland

Modern video streaming services require quality assurance of the presented audiovisual material. Quality assurance mechanisms allow streaming platforms to provide quality levels that are considered sufficient to yield user satisfaction, with the least possible amount of data transferred. A variety of measures and approaches have been developed to control video quality, e.g., by adapting it to network conditions. These include objective matrices of the quality and thresholds identified by means of subjective perceptual judgments. The former group of matrices has recently gained the attention of (multi)media researchers. They call this area of study "Quality of Experience" (QoE). In this paper, we present a review of QoE’s theoretical models together with a discussion of their properties and implications for the field. We argue that most of them represent the bottom-up approach to modeling. Such models focus on describing as many variables as possible, but with a limited ability to investigate the causal relationship between them;therefore, the applicability of the findings in practice is limited. To advance the field, we therefore propose a structural, top-down model of video QoE that describes causal relationships among variables. We hope that our framework will facilitate designing comparable experiments in the domain. Copyright © 2023, The Authors. All rights reserved.

关键词： Quality assurance

Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

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arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Liu, Yinqiu Wang, Jiacheng Lin, Yijing Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Cui, Shuguang Ai, Bo Zhou, Haibo Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Shenzhen China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China School of Electronic Science and Engineering Nanjing University Jiangsu Nanjing210093 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across various applications. The ability to model complex data distributions and generate high-quality samples has made GDMs particularly effective in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, which involves a series of noise addition and denoising steps, is a powerful and unique approach to learning and generating data. This paper serves as a comprehensive tutorial on applying GDMs in network optimization tasks. We delve into the strengths of GDMs, emphasizing their wide applicability across various domains, such as vision, text, and audio generation. We detail how GDMs can be effectively harnessed to solve complex optimization problems inherent in networks. The paper first provides a basic background of GDMs and their applications in network optimization. This is followed by a series of case studies, showcasing the integration of GDMs with Deep Reinforcement Learning (DRL), incentive mechanism design, Semantic communications (SemCom), Internet of Vehicles (IoV) networks, etc. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design. We conclude with a discussion on potential future directions for GDM research and applications, providing major insights into how they can continue to shape the future of network optimization. © 2023, CC BY.

关键词： Reinforcement learning

Classification and Recognition of Underwater Target Based on MFCC Feature Extraction

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Classification and Recognition of Underwater Target Based on...

IEEE International Conference on Signal Processing, communications and Computing (ICSPCC)

作者： Yuze Tong Xin Zhang Yizhou Ge School of Marine Science and Technology Northwestern Polytechnical University Xi’an China Science and Technology on Communication Information Security Control Laboratory NO.36 Research Institute of CETC Jiaxing China

ISBN: (数字)9781728172026

ISBN: (纸本)9781728172033

The key to underwater target recognition is to extract the effective features of underwater target radiation noise. This paper presents an effective method for underwater target recognition and classification by extracting Mel-Frequency Cepstral Coefficients (MFCCs) features of underwater target radiation noise. Compared with traditional spectral analysis methods, MFCC makes full use of the non-linear auditory effect of the human ear with different perception capabilities for sounds of different frequencies. In this paper, the classification experiment of the radiated noise of the three types of measured underwater targets is done, where the MFCC feature vectors of the three types of targets are extracted, and the K-Nearest Neighbor (K-NN) algorithm is used to classify and identify them. Finally, the experimental results show that the method is effective.

关键词： Feature extraction Mel frequency cepstral coefficient Target recognition Classification algorithms Filter banks Ear Auditory system

Unified Authentication Scheme for IoT Blockchain Based on PUF

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Unified Authentication Scheme for IoT Blockchain Based on PU...

IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Dawei Li Yingxian Song Lixin Zhang Di Liu Baoquan Ma Zhenyu Guan School of Cyber Science and Technology Beihang University Beijing China National Engineering Laboratory for Industry Control System Information Security Technology Beijing China National Computer System Enginering Research Institute of China Beijing China

The number of global Internet of Things devices has increased rapidly and has a wide range of application markets. Access authentication methods for massive heterogeneous IoT devices are complicated, and central servers and trusted platforms cannot take effective measures against tampered devices. Analyzing the problems and challenges faced by IoT devices, this paper proposes a unified authentication scheme for IoT blockchain devices based on PUF. The PUF model is used to authenticate IoT devices, and the model parameters are decomposed into various parts and stored in each node in the blockchain. The homomorphic hash function is used to aggregate the partial authentication response values generated by the distribution in the invisible case to complete the authentication of the device information. It solves the complex and diverse problems of device authentication schemes and realizes the credibility and security of devices data sources and devices information storage stability. Finally, the functional analysis confirmed that the scheme is practical and executable.

关键词： Hash functions Soft sensors Authentication Stability analysis Functional analysis Blockchains security

Capacity Maximization for FAS-assisted Multiple Access Channels

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arXiv 2023年

作者： Xu, Hao Wong, Kai-Kit New, Wee Kiat Ghadi, Farshad Rostami Zhou, Gui Murch, Ross Chae, Chan-Byoung Zhu, Yongxu Jin, Shi The Department of Electronic and Electrical Engineering University College London LondonWC1E7JE United Kingdom Yonsei Frontier Laboratory Yonsei University Seoul03722 Korea Republic of Erlangen91054 Germany Hong Kong University of Science and Technology Clear Water Bay Hong Kong The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of The School of Engineering University of Warwick Coventry United Kingdom The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China

This paper investigates a multiuser millimeter-wave (mmWave) uplink system in which each user is equipped with a multi-antenna fluid antenna system (FAS) while the base station (BS) has multiple fixed-position antennas. Our primary objective is to maximize the system capacity by optimizing the transmit covariance matrices and the antenna position vectors of the users jointly. To gain insights, we start by deriving upper bounds and approximations for the capacity. Then we delve into the capacity maximization problem. Beginning with the simple scenario of a single user equipped with a single-antenna FAS, we demonstrate that a closed-form optimal solution exists when there are only two propagation paths between the user and the BS. In the case where multiple propagation paths are present, a near-optimal solution can also be obtained through a one-dimensional search method. Expanding our focus to multiuser cases, in which users are equipped with either single- or multi-antenna FAS, we show that the original capacity maximization problems can be reformulated into distinct rank-one programmings. Then, we propose alternating optimization algorithms to deal with the transformed problems. Simulation results indicate that FAS can improve the capacity of the multiple access channel (MAC) greatly, and the proposed algorithms outperform all the benchmarks. Copyright © 2023, The Authors. All rights reserved.

关键词： Covariance matrix

Network security Situation Awareness technology Based on Multi-source Heterogeneous Data

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Network Security Situation Awareness Technology Based on Mul...

2020 International Conference on Cyberspace Innovation of Advanced Technologies, CIAT 2020

作者： Zhang, Daojuan Qian, Kexiang Wang, Wenhui Fang, Fuyang Wang, Chonghua Luo, Xi State Grid Key Laboratory of Information and Network Security Global Energy Interconnection Research Institute Co. Ltd Beijing China Information Science Academy China Electronics Technology Group Corporation Beijing China Department of Security Technology China Industrial Control Systems Cyber Emergency Response Team Beijing China Cyber Space Institute of Advanced Technology Guangzhou University Guangzhou China

ISBN: (纸本)9781450387828

With the development of information technology, the scale of the network continues to expand, and the security issues continue to increase. The complexity of the network security situation is increasing and the importance of the network security situational awareness continues to increase. The data sources are wide, the type and the number are large in a large-scale network environment currently. This paper comprehensively studies the network security situational awareness technology based on multi-source heterogeneous data. In addition, this paper introduces the origin, concept and the model of the network situational awareness, as well as the characteristics of network security situational awareness based on multi-source heterogeneous data fusion. Finally, the key technologies in the security situational awareness such as the extraction of situational elements, multi-source data fusion, situation assessment, situation prediction and visual display are introduced. © 2020 ACM.

关键词： Data fusion

Multi-objective particle swarm optimization with adaptive strategies for feature selection

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Swarm and Evolutionary Computation 2021年 62卷 100847-100847页

作者： Han, Fei Chen, Wen-Tao Ling, Qing-Hua Han, Henry School of Computer Science and Communication Engineering Jiangsu University ZhenjiangJiangsu212013 China Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace ZhenjiangJiangsu212013 China School of Computer Science Jiangsu University of Science and Technology ZhenjiangJiangsu212003 China Department of Computer and Information Sciences Fordham University NY48105 United States

Feature selection is a multi-objective optimization problem since it has two conflicting objectives: maximizing the classification accuracy and minimizing the number of the selected features. Due to the lack of selection pressures, most feature selection algorithms based on multi-objective optimization obtain many optimal solutions around the center of Pareto fronts. The penalty boundary interaction (PBI) decomposition approach provides fixed selection pressures for the population, but fixed selection pressures are hard to solve feature selection problems with complicated Pareto fronts. This paper proposes a novel feature selection algorithm based on multi-objective particle swarm optimization with adaptive strategies (MOPSO-ASFS) to improve the selection pressures of the population. An adaptive penalty mechanism based on PBI parameter adjusts penalty values adaptively to enhance the selection pressures of the archive. An adaptive leading particle selection based on feature information combines the opposite mutation and the feature frequencies to improve the selection pressure of each particle. The proposed algorithm is compared with 6 related algorithms on 14 benchmark UCI datasets and 6 gene datasets. The experimental results show that MOPSO-ASFS can find optimal solutions with better convergence and diversity than comparison algorithms especially on the high dimensional datasets. © 2021 Elsevier B.V.

关键词： Multiobjective optimization

Safeguarding Next Generation Multiple Access Using Physical Layer security Techniques: A Tutorial

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arXiv 2024年

作者： Lv, Lu Xu, Dongyang Hu, Rose Qingyang Ye, Yinghui Yang, Long Lei, Xianfu Wang, Xianbin Kim, Dong In Nallanathan, Arumugam The State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China The School of Information and Communications Engineering Xi’an Jiaotong University Xi’an710049 China The Department of Electrical and Computer Engineering Utah State University LoganUT84322 United States The Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts & Telecommunications Xi’an710121 China The School of Information Science and Technology Southwest Jiaotong University Chengdu610031 China The Department of Electrical and Computer Engineering Western University LondonONN6A 5B9 Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of School of Electronic Engineering and Computer Science Queen Mary University of London E1 4NS United Kingdom

Driven by the ever-increasing requirements of ultrahigh spectral efficiency, ultra-low latency, and massive connectivity, the forefront of wireless research calls for the design of advanced next generation multiple access schemes to facilitate provisioning of these stringent demands. This inspires the embrace of non-orthogonal multiple access (NOMA) in future wireless communication networks. Nevertheless, the support of massive access via NOMA leads to additional security threats, due to the open nature of the air interface, the broadcast characteristic of radio propagation as well as intertwined relationship among paired NOMA users. To address this specific challenge, the superimposed transmission of NOMA can be explored as new opportunities for security aware design, for example, multiuser interference inherent in NOMA can be constructively engineered to benefit communication secrecy and privacy. The purpose of this tutorial is to provide a comprehensive overview on the state-of-the-art physical layer security techniques that guarantee wireless security and privacy for NOMA networks, along with the opportunities, technical challenges, and future research trends. Copyright © 2024, The Authors. All rights reserved.

关键词： Radio waves

A Analysis of Attack and Defense Mobile Ad Hoc Network Based on OPNET

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A Analysis of Attack and Defense Mobile Ad Hoc Network Based...

2019 International Conference on Advanced Material Research and Processing technology, AMRPT 2019

作者： Dai, Jiahao Xu, Xiaofeng Science and Technology on Communication Information Security Control Laboratory Zhejiang Jiaxing China China Electronic Group Corporation No.36 Institute Zhejiang Jiaxing China

Due to the broadcast nature of wireless communications, the damage to mobile ad hoc networks is becoming more and more common. We propose a network stability model that can effectively reflect the network performance when the network is damaged in real time. The Ad Hoc network model is built by using the node model supporting the IEEE802.11 standard provided by OPNET software to simulate the network performance of the network under different degrees of damage. This model provides an effective way for the simulation analysis of network performance under the condition of Ad Hoc network damage. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Mobile ad hoc networks