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

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MSAF: A Multi-Scale Attention-Fusion Model for Long-Term Cell-Level network Traffic Prediction 6

MSAF: A Multi-Scale Attention-Fusion Model for Long-Term Cel...

引用

6th International conference on Electrical, control and Instrumentation Engineering, ICECIE 2024

作者： Ma, Xuesen Li, Jingqi Li, Dacheng Li, Yangyu Qiao, Yan School of Computer Science and Information Engineering Hefei University of Technology Hefei China Hefei University of Technology Intelligent Interconnected Systems Laboratory of Anhui Province Hefei230009 China Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China Hefei University of Technology Hefei China

ISBN: (纸本)9798350380040

Implementing precise network traffic prediction is essential for optimizing base station strategies, allocating network resources effectively, reducing costs, and ensuring service quality in network management. Currently, most mainstream forecasting methods primarily focus on either the time domain or the frequency domain, attempting to capture and express time series data features from a one-dimensional perspective. This one-dimensional approach can be limiting, as relying solely on a single dimension may lead to incomplete or suboptimal modeling, it fails to fully capture the intricate interactions between time-domain and frequency-domain that define network traffic behaviors. To address this, we propose a novel Multi-Scale Attention-Fusion (MSAF) model. The key module in MSAF, named Attention-Fusion, integrates both time-domain and frequency-domain features of network traffic data. This effectively addresses the limitations of previous attention mechanisms in simultaneously identifying frequency components and temporal patterns, providing enhanced modeling capabilities for complex network traffic data. Additionally, the Attention-Fusion module utilizes a DSConv module combined with the attention mechanism to identify correlations between sequences of different lengths. Evaluation of MSAF on two real-world network traffic datasets demonstrates that MSAF outperforms other mainstream methods in terms of forecasting performance. © 2024 IEEE.

关键词： Time series

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Data-Driven network Path Simulation with iBox 22

Data-Driven Network Path Simulation with iBox

引用

2022 ACM SIGMETRICS/IFIP performance Joint International conference on Measurement and Modeling of Computer systems, SIGMETRICS/performance 2022

作者： Ashok, Sachin Tiwari, Shubham Natarajan, Nagarajan Padmanabhan, Venkata N. Sellamanickam, Sundararajan University of Illinois at Urbana-Champaign ChampaignIL United States Microsoft Research India Bengaluru India

ISBN: (纸本)9781450391412

While network simulation is widely used for evaluating network protocols and applications, ensuring realism remains a key challenge. There has been much work on simulating network mechanisms faithfully (e.g., links, buffers, etc.), but less attention on the critical task of configuring the simulator to reflect reality. We present iBox ("internet in a Box"), which enables data-driven network path simulation, using input/output packet traces gathered at the sender/receiver in the target network to create a model of the end-to-end behaviour of a network path. Our work builds on recent work in this direction [2, 6] and makes three contributions: (1) estimation of a lightweight non-reactive cross-traffic model, (2) estimation of a more powerful reactive cross-traffic model based on Bayesian optimization, and (3) evaluation of iBox in the context of congestion control variants in an internet research testbed and also controlled experiments with known ground truth. This paper represents an abridged version of [3]. © 2022 Owner/Author.

关键词： cross-traffic estimation data-driven simulation bayesian optimization

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performance Evaluation of an internet-of-Things Platform Based on Open-Source

Performance Evaluation of an Internet-of-Things Platform Bas...

引用

8th International conference on Science, Technology and Innovation for Society, CITIS 2023

作者： Guillén, José Francisco Sigua, Johnny Mauricio Zambrano, Julio César Salesian Polytechnic University Calle Vieja 12-30 and Elia Liut Cuenca Ecuador

ISBN: (纸本)9783031519819

This paper presents the performance evaluation of an open-source IoT platform. The platform has a three-layer architecture. The physical layer comprises the elements for data acquisition and process automation. The communication layer consists of a set of equipment that facilitates the exchange of information between the control devices and the application layer. The application layer is based on a container architecture and facilitates the interaction between the user and the processes. A ThingsBoard service is executed on a container and data is transmitted using the Message Queuing Telemetry Transport (MQTT) protocol. Additionally, a database service was implemented in PostgreSQL using another container. The evaluation of the implemented platform was performed through two virtual processes created in Tecnomatix Plant Simulation software. Each process was automated with a virtualized version of a SIEMENS S7-1500 PLC available through the SIMATIC S7-PLCSIM Advanced software tool. A set of Key performance Indicators (KPIs) generated in both processes are visualized and managed in the Things-Board application. The performance of the platform has been evaluated based on the bandwidth present at the network layer and the resources consumed by the services running on the containers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Containers

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MemADet: A Representative Memory Bank Approach for Industrial Image Anomaly Detection

MemADet: A Representative Memory Bank Approach for Industria...

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2024 IEEE International conference on systems, Man, and Cybernetics, SMC 2024

作者： Li, Min He, Jinghui Ying, Zuobin Li, Gang Zhou, Mingle Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China City University of Macau Faculty of Data Science China

ISBN: (纸本)9781665410205

In the field of industrial production, anomaly detection is crucial for ensuring product quality and maintaining production efficiency. With the continuous advancement of computer vision technology, it has shown tremendous potential in industrial applications. However, the scarcity of labeled anomaly samples in real-world operating environments poses significant challenges for traditional anomaly detection techniques. To address this, we propose MemADet, a novel anomaly detection model that employs an unsupervised approach and leverages a representative memory bank. It employs a dynamic decision mechanism to control the representativeness of the features stored in the memory bank, and employs a weighted anomaly score calculation mechanism to further enhance the performance of image anomaly detection. Our evaluations indicate that MemADet performs robustly in industrial image anomaly detection across three datasets, with particularly no-table detection accuracy on the MVTec AD dataset. Its efficacy is further validated by competitive results on two additional datasets, highlighting its consistent and effective performance in various settings. © 2024 IEEE.

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Speech Enhancement Based on Two-Stage Neural network with Structured State Space for Sequence Transformation 13th

Speech Enhancement Based on Two-Stage Neural Network with St...

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13th International conference on High-performance Computing systems and Technologies in Scientific Research, Automation of control and Production, HPCST 2023

作者： Lependin, Andrey Karev, Valentin Nasretdinov, Rauf Ilyashenko, Ilya AltSU – Altai State University Lenin Avenue 61 Barnaul656049 Russia

ISBN: (纸本)9783031510564

In this paper, a new method for improving speech quality using the Structured State Space for Sequence (S4) transformation was proposed. This method inherits existing two-stage denoising methods using recurrent neural networks. However, the use of S4 layers instead of long-term short-term memory brought improvements in two ways. Firstly, it was possible to achieve a reduction in the number of trained parameters of the neural network, while maintaining the quality of speech enhancement. Secondly, due to the use of the convolutional representation of S4 transformations, the network training time per one epoch has decreased. The proposed two-stage neural network model for denoising was implemented using the PyTorch library. For training and testing, a standard DNS Challenge 2020 dataset was used. The optimal type of the loss function for training, and the best number of S4 layers was selected. Comparison with existing real-time speech enhancement methods showed that the developed model was one of the best performers for all quality metrics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Signal processing

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Simulation of Large-Scale 5G Communication Optimization Model Based on Fuzzy Neural network Optimization Algorithm

Simulation of Large-Scale 5G Communication Optimization Mode...

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2023 International conference on Power, Electrical Engineering, Electronics and control, PEEEC 2023

作者： Zhou, Xiangling Lv, Su Luo, Xian Li, Xiang Huang, Chao Information & Communication Branch of Hubei Epc Hubei Wuhan430000 China

ISBN: (纸本)9798350329124

With the rapid development of internet of Things (IoT) technology, the demand for machine communication (MTC) is increasing. The traditional cellular mobile communication system designed and built for human communication (HTC) will not meet the communication needs of MTC. At the same time, due to the huge number of users and the expanded network scale, the energy consumption of wireless communication network system is on the rise. The environmental pollution caused by greenhouse gas emissions generated by wireless communication systems and the accompanying huge energy consumption have attracted wide attention of operators and the whole society. This article briefly introduces the development of 5G wireless communication systems, comprehensively summarizes the spectrum allocation of millimeter waves, channel propagation characteristics, channel measurement methods, channel detectors, channel parameter estimation algorithms, channel modeling methods, and standardized channel models. A large number of multi band and multi scene millimeter wave channel measurements have been conducted. Experiments were conducted using UCI datasets and engineering examples, and compared with traditional cloud models, fuzzy neural networks, and BP neural networks to analyze the operational efficiency, accuracy, and number of rules of the algorithm. In addition, computer simulation further verifies that the proposed method can achieve better performance compared to several existing codebook design methods. © 2023 IEEE.

关键词： Fuzzy neural networks

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performances evaluation and Congestion Analysis in IoT network: Simulation and Emulation approach 2

Performances evaluation and Congestion Analysis in IoT Netwo...

引用

2nd IEEE International Mediterranean conference on Communications and networking, MeditCom 2022

作者： Benadji, Hanane Zitoune, Lynda Veque, Veronique Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes Gif-sur-Yvette91190 France

ISBN: (数字)9781665498258

ISBN: (纸本)9781665498258

The age of the massive internet of Things (IoT) is forthcoming, transforming real-world objects into intelligent virtual objects and offering practical and high-quality innovative services. The Constrained Application Protocol (CoAP) was adopted as an efficient candidate to transmit collected data over-constrained environments. However, the congestion control scheme of CoAP and its advanced versions still do not cope with the massive deployment of heterogeneous devices and simultaneous transmission, which increases congestion implying the unsatisfactory of many applications with various requirements and the energy-efficiency reduction. As the first step in our study to improve the CoAP congestion control, we deeply analyzed in this work the network performance when CoAP congestion control operates in an IoT network. We varied several parameters at different levels: the network, the CoAP protocol itself, and the node processing capacity. This performance analysis is performed by simulation under Cooja/Contiki. Obtained results show the limitations of CoAP and the need to adjust the parameters of CoAP, whether the network state is congested or not. © 2022 IEEE.

关键词： internet of things

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Lightweight Cryptography Model for Overhead and Delay Reduction in the network 4th

Lightweight Cryptography Model for Overhead and Delay Reduct...

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4th EAI International conference on Cognitive Computing and Cyber Physical systems, IC4S 2023

作者： Yamparala, Rajesh Kamaleshwar, T. Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Tamil Nadu Chennai600062 India

ISBN: (纸本)9783031488870

Mobile Ad hoc network (MANET) refers to a group of multi-hop wireless networks that can configure themselves. The success of MANET-based applications hinges on a number of criteria, with reliability being a key one. While many security procedures already exist, the new characteristics and vulnerabilities of this networking paradigm may make the old ones obsolete. The ability of a network to scale up in size without sacrificing performance is known as scalability. Proactive routing algorithms in mobile wireless networks face a significant scalability difficulty due to the frequent need to send and receive control signals. The key to fixing the scalability issue is cutting down on overhead. In order to lessen the burden of data transmission, a overhead and delay reduction model is designed in this research. The suggested technique is based on a weight function that integrates the node's connection and battery life. In this research, MANET network latency and traffic load reduction model is designed. The proposed technique is based on the idea of only transmitting certain, predetermined packets avoiding loss. Congestion in the network can be avoided by first ensuring that all neighbor nodes are valid before sending a packet. When it comes to the evolution of MANET, quality of Service (QoS) is a crucial factor. This research proposes a Trusted Node Feedback based Node Authentication Model with Node Transmission Analysis (NAM-NTA) model for decreasing the network overhead and delay levels in the MANET. The emphasis of this research is on constraints based on latency and neighbor connectivity. This technique is able to detect superfluous connections and eliminate them from the network structure. The proposed achieved 98.3% accuracy in network delay reduction. The proposed model is compared with the traditional model and the results show that the proposed model performance in overhead and delay reduction is high. © 2024, ICST Institute for Computer Sciences, Social Informa

关键词： quality of service

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Impact of Patch Array Antenna Size and Beampattern on Wireless network Capacity 1

Impact of Patch Array Antenna Size and Beampattern on Wirele...

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1st Asian conference on Communication and networks, ASIANComNet 2024

作者： Geranmayeh, Parmida Grass, Eckhard Humboldt University of Berlin Faculty of Mathematics and Natural Sciences Department of Computer Science Berlin Germany Germany

ISBN: (纸本)9798350367003

Rectangular patch antennas are important components in modern wireless communication systems, including 5 G and emerging 6 G technologies. These antennas support highfrequency, high-capacity, and energy-efficient wireless communication. For beamforming, the dimensions of these antennas significantly influence their radiation patterns, and antenna gain. Beamforming technology is essential for 5G and 6G networks, enhancing coverage, capacity, and energy efficiency. Effective beamforming relies on array configurations of rectangular patch antennas, with precise control over antenna patterns to improve signal quality and minimize interference. This article explores the impact of the size of rectangular patch array antenna in the mmWave frequency band. The primary goal is to maximize channel capacity between transmitters and receivers. Our study involves simulations using discretized antenna patterns for various patch array antenna sizes, based on realistic room models and a ray-tracing approach. The results demonstrate that larger antenna arrays can significantly increase network capacity. However, selecting the optimal steering vectors for all antennas becomes more complex with increasing antenna size, but is essential for achieving the best configuration. © 2024 IEEE.

关键词： Slot antennas

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SIP-Net: A Shift Interactive Perception network for Single Image Dehazing 43

SIP-Net: A Shift Interactive Perception Network for Single I...

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43rd Chinese control conference, CCC 2024

作者： Li, Fuping Xie, Siying Ju, Mingye Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing210000 China

ISBN: (纸本)9789887581581

Learning-based methods have demonstrated their effectiveness in image dehazing tasks. Recent variants of Swin Transformer have made significant progress in image dehazing. However, they limit the self-attention (SA) calculation within each window, which reduces the image dehazing performance. To overcome this question, we propose a Shift Interactive Perception network (SIP-Net) in this paper for image dehazing. Specifically, we first use a Shift Convolution Block (SCB) to effectively extract local information of image features. Next, to the interdependence of channel features for more powerful feature relevance learning, we embed a Second-order Attention Block (SAB) into SIP-Net. Following the SAB, we propose an Interactive Perceptual Block (IPB) involving a three-branch architecture. To capture the complex dependencies of the whole image, the upper branch adopts a recurrent cross-attention block, which can effectively model the contextual information of all pixels. The bottom branch extracts feature maps while increasing their edge details using a simple and efficient encoding-decoding architecture. To improve the representation, the middle branch adaptively updates the characteristics based on the outputs of the top and lower branches. Extensive evaluations on synthetic and real-world datasets demonstrate that our SIP-Net outperforms other state-of-the-art dehazing methods. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Demulsification

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