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H-STEP: Heuristic Stable Edge Service Entity Placement for Mobile Virtual Reality Systems

IEEE Transactions on Mobile Computing 2025年

作者： Chi, Xuejian Chen, Honglong Ni, Zhichen Sun, Haiyang Sun, Peng Yu, Dongxiao Shandong Provincial Engineering Research Center of Intelligent Sensing and Measurement and Control Technology College of Control Science and Engineering Qingdao266580 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Shandong University School of Computer Science and Technology Qingdao266237 China

Virtual reality (VR) technology, as a latency-sensitive application, can achieve real-time response to enhance the user's quality of experience (QoE) on edge devices. However, edge servers, unlike internally managed cloud servers, are prone to hardware failures, software abnormalities, and network attacks. Most prior studies have focused on reducing service delay and improving user coverage through service entity (SE) placement, often neglecting the critical impact of edge server malfunctions on user QoE. In this work, we design a stable service entity placement framework that connects users on faulty servers to collaborative edge servers, ensuring seamless task completion. This framework presents two primary challenges: determining the grouping of collaborative edge services and the placement of SEs. To address these challenges, we introduce a heuristic stable service entity placement (H-STEP) scheme. This scheme first determines the grouping of collaborative edge servers using an iterative search algorithm and then places SEs on suitable edge servers via a fast non-dominated sorting genetic placement algorithm. This approach balances stability benefits with total cost, enhancing the system's economic benefits. We theoretically analyze the performance of H-STEP and derive the performance gap between H-STEP and the optimal scheme. Extensive real-data-driven simulations demonstrate that H-STEP's performance closely approximates that of the optimal scheme and surpasses existing schemes. © 2002-2012 IEEE.

关键词： Virtual environments

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Parallel Graph Attention Network Model Based on Pixel and Superpixel Feature Fusion for Hyperspectral Image Classification

Parallel Graph Attention Network Model Based on Pixel and Su...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Lisong Ma Qingyan Wang Junping Zhang Yujing Wang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

With the development of hyperspectral sensors, there is an increasing amount of accessible hyperspectral data, and the classification task for land cover categories has gained significant attention. Existing classification methods typically extract features from either the pixel or superpixel perspective. However, using a single-scale feature extraction approach fails to simultaneously consider both local and global features of land cover, leading to suboptimal classification results. To address this issue, this paper proposes a parallel graph attention network model based on pixel and superpixel feature fusion (SSPGAT) for hyperspectral image classification, which leverages the fusion of pixel-level and superpixel-level features. The proposed approach first employs spectral convolutional layers to reduce the redundant spectral dimension. Then, it utilizes graph attention network (GAT) to extract local and global features of land cover separately from the pixel and superpixel perspectives. Finally, a fully connected network is employed to classify the fused features from both branches. Experimental results on two different datasets demonstrate the effectiveness of the proposed approach.

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Spectrum Sensing for Cognitive Radio Based on Feature Extraction and Deep Learning 11

Spectrum Sensing for Cognitive Radio Based on Feature Extrac...

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2022 11th International Conference on Information and Electronics engineering, ICIEE 2022

作者： Geng, Yue Huang, Jingyi Yang, Jianxin Zhang, Sen School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518061 China School of Mechanical Engineering & Automation Beihang University Beijing100191 China School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin150080 China

In cognitive radio, spectrum sensing is used to determine whether the primary user is using the spectrum based on the signal received on a specific frequency band, thereby determining whether the secondary user can use the spectrum. The main problem faced by spectrum sensing is how to identify the existence of the primary signal under the condition of low signal-to-noise ratio (SNR). Compared with traditional technologies, deep learning methods can identify the features of input data more efficiently and accurately. Based on convolutional neural network (CNN), This paper regard spectrum sensing as a binary classification problem. In the method we proposed, different features of received are extracted, and a dataset of feature matrices obtained under different SNRs is constructed for the training of the CNN network. Experiment results show that under the condition of low signal-to-noise ratio, the performance of our method is improved compared with the traditional method, and the combination of different features can improve the sensing accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Cognitive radio

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Study on Dynamic Behavior of $\text{SF}_{6}/\mathrm{N}_{2}$ Discharge Under Narrow-Gap Uniform Electric Field

Study on Dynamic Behavior of $\text{SF}_{6}/\mathrm{N}_{2}$ ...

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International Conference on Electric Power Equipment - Switching technology (ICEPE-ST)

作者： Yingli Wang Dongyue Cao Mingquan Zhang Qiming Lu Dianchun Zheng College of Measurement and Communication Harbin University of Science and Technology Harbin China School of Electrical and Electronic Engineering Harbin University of Science and Technology Harbin China

ISBN: (数字)9798350388947

ISBN: (纸本)9798350388954

In this paper, a hydrodynamic model of narrow-gap $\text{SF}_{6}/\mathrm{N}_{2}$ gas discharge with flat electrode configuration was established, and the microscopic behavior characteristics of sulfur hexafluoride gas discharge under uniform electric field conditions were strictly studied, and the whole process of discharge triggering, generation of charged particles, particle adhesion, particle recombination, and evolution of discharge trajectory until gap breakdown was revealed. What's more, different discharge triggering conditions were further explored, and the influence mechanism of the initial seed electron density on the model discharge process was investigated in detail. The research results showed that the initial seed electron group density peak N0 was tightly correlated to the spatial charged particles, the gap electric field distribution, and the evolution of the discharge trajectory. Although the initial seed electron group position Z0 has a certain effect on the microscopic behavior of discharge, it is mainly reflected in the spatiotemporal scale of the streamer development process.

关键词： Spontaneous emission Sulfur hexafluoride Switches Electron mobility Hydrodynamics Discharges (electric) Trajectory Electron microscopy Electric fields Electrons

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Multi-branch low-light enhancement algorithm based on spatial transformation

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Multimedia Tools and Applications 2024年第18期84卷 1-21页

作者： Wang, Wenlu Sun, Ying Zou, Chunlong Tang, Dalai Fang, Zifan Tao, Bo Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China School of Computer Information Management Inner Mongolia University of Finance and Economics Hohhot010051 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Hydroelectric Design & amp Maintenance China Three Gorges University Yichang443002 China

Many state-of-the-art low-light image enhancement techniques now suffer from issues like color distortion, detail blurring, and the halo effect, hindering their ability to produce visual effects. This paper presents a multi-branch low-light enhancement algorithm based on spatial transformation to significantly improve the visual impact of images under low-light settings, overcoming the limitations of existing approaches. The process involves dividing the initial low-light picture into three distinct layers. Bootstrap filtering and Contrast Limited Adaptive Histogram Equalization are used to process the main feature layer. Primary feature extraction is used to extract features for the compensation layer, which is then integrated with Contrast Limited Adaptive Histogram Equalization and MSRCR. The auxiliary layer utilizes spatial transformation to apply gamma correction to the V-channel and performs color space transformation and additional processing. Ultimately, these three layers are combined and refined to create the final improved image. Based on the experimental results, the proposed method outperforms the standard MSRCR algorithm by 52.47%, 71.58%, and 12.10%, respectively, on the assessment metrics AG, SD, and IE. LOE declines by 22.3%. The processed image presents a good visual quality, effectively enhancing the image brightness while retaining a large amount of information and improving the image details. This paper proposes an effective method to deal with the problem of low illumination image enhancement, which provides a strong reference for future research and application in related fields. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image enhancement

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Graph Convolutional Networks with Visual Masking and Social Interaction Models for Pedestrian Trajectory Prediction

Graph Convolutional Networks with Visual Masking and Social ...

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Consumer Electronics and Computer engineering (ICCECE), 2021 IEEE International Conference on

作者： Guopei Zeng Luping Wang School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China Zhejiang Aerospace Runbo Measurement and Control Technology Co. Ltd Zhejiang China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

Pedestrian trajectory prediction is critical for autonomous driving, crowd analysis, and urban surveillance. To address insufficient interaction modeling in existing methods, we propose two enhancements. First, a field-of-view(FoV)-aware masking mechanism filters irrelevant interactions by dynamically adjusting to pedestrian distances and motion directions. Second, we introduce a more detailed modeling of the influence among pedestrians, replacing the traditional modeling based on reciprocal of distance. This model, integrated with FoV masks to construct sparse adjacency matrices for graph convolution. A temporal convolutional network then predicts trajectories as bivariate Gaussian distributions. Evaluations on ETH and UCY benchmarks demonstrate the effectiveness of our method.

关键词： Analytical models Visualization Pedestrians Filters Surveillance Predictive models Benchmark testing Vectors Trajectory Sparse matrices

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Potential Transmission Choice for Internet of Things(IoT):Wireless and Batteryless communications and Open Problems

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China communications 2021年第2期18卷 241-249页

作者： Zhan Xu Guanjie Hu Minzheng Jia Lan Dong School of Information and Communication Engineering and with Key Laboratory of Modern Measurement&Control Technology Ministry of EducationBeijing Information Science&Technology UniversityChina Beijing Key Lab of Transportation Data Analysis and Mining School of Computer and Information TechnologyBeijing Jiaotong UniversityBeijingChina Department of Information Engineering Beijing Polytechnic CollegeBeijingChina

The 5th generation mobile communications aims at connecting everything and future Internet of Things(IoT)will get everything smartly *** realize it,there exist many *** key challenge is the battery problem for small devices,such as sensors or *** backscatter,also referred to as or battery-free backscatter,is a new potential technology to address this *** early and typical type of batteryless backscatter is ambient ***,batteryless backscatter utilizes environmental wireless signals to enable battery-free devices to communicate with each *** devices first harvest energy from ambient wireless signals and then backscatter these signals so as to transmit their own *** paper reviews the current studies about batteryless backscatter,including various backscatter schemes and theoretical works,and then introduces open problems for future research.

关键词： batteryless backscatter battery-free channel state information(CSI) channel estimation multiple antennas signal detection symbiotic communication

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Zero-Order-Term Suppression in Off-Axis Digital Holography Based Onbinary Kronecker-Product Image Interpolation

SSRN

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SSRN 2024年

作者： Yu, Xuelian Xie, Zhenfei Bao, Xingxu Niu, Jia Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin150080 China Harbin University of Science and Technology China

Off-axis digital holography can reconstruct the amplitude and phase of the imaging object by selecting the original term spectrum through filtering. A larger filtering range contains more effective information from the original term spectrum. However, the presence of zero-order term limits the size of the filter window and consequently affects the resolution of reconstruction. In this work, we propose a spliced spectrum method based on binary Kronecker-product image interpolation to better suppress zero-order term and improve the quality of reconstruction. Additionally, a rectangular Butterworth filter is also introduced to make the reconstructed images smoother and more regular. We demonstrate the feasibility of this method through simulations of a picture and experiments with two different imaging objects. © 2024, The Authors. All rights reserved.

关键词： Interpolation

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Three-Dimensional Numerical Simulation on Flow-Induced Vibration of Condenser Tube Bundles

Three-Dimensional Numerical Simulation on Flow-Induced Vibra...

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2021 OES China Ocean Acoustics, COA 2021

作者： Li, Yuelin Sun, Chao Liu, Yuechan Ai, Shiqin Harbin University of Science and Technology Harbin School of Measurement-Control Technology and Communication Engineering China Harbin City150080 China

ISBN: (纸本)9781728181905

Taking the heat exchange tube in the condenser as the research object, the three-dimensional finite element model of the heat exchange tube and the Internal and external fluid of pipe is established, and the bidirectional fluid-solid coupling calculation of the heat exchange tube is carried out. The time-domain and frequency-domain curves of lift, drag and displacement of the heat exchange tube and the time-domain and frequency-domain curves of the pressure pulsation in the tube are obtained. At the same time, the acoustic simulation calculation is carried out for the vibration noise of the heat exchange tube. The time domain and frequency domain curves of sound pressure near the heat exchange tube are obtained. The simulation results show that the frequency of pressure pulsation corresponds to the frequency of lift and drag. The flow velocity in the tube studied in this paper will affect the amplitude and waveform of the pressure pulsation but will not affect its frequency. The sound pressure frequency of the upper and lower sides of the heat exchange tube only corresponds to the lift frequency, and the sound pressure frequency on the left and right side corresponds to the lift and drag frequencies. © 2021 IEEE.

关键词： Flow velocity

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Dissecting the contributions of organic nitrogen aerosols to global atmospheric nitrogen deposition and implications for ecosystems

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National Science Review 2023年第12期10卷 124-136页

作者： Yumin Li Tzung-May Fu Jian Zhen Yu Xu Yu Qi Chen Ruqian Miao Yang Zhou Aoxing Zhang Jianhuai Ye Xin Yang Shu Tao Hongbin Liu Weiqi Yao Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks School of Environmental Science and Engineering Southern University of Science and Technology Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area Southern University of Science and Technology Division of Environment and Sustainability Hong Kong University of Science and Technology National Center for Applied Mathematics Shenzhen Department of Chemistry Hong Kong University of Science and Technology State Key Joint Laboratory of Environmental Simulation and Pollution Control International Joint Laboratory for Regional Pollution Control College of Environmental Sciences and Engineering Peking University Frontier Science Center for Deep Ocean Multispheres and Earth System and Physical Oceanography Laboratory Ocean University of China College of Oceanic and Atmospheric Sciences Ocean University of China Department of Ocean Science Hong Kong University of Science and Technology Department of Ocean Science and Engineering Southern University of Science and Technology

Atmospheric deposition of particulate organic nitrogen（ONp） is a significant process in the global nitrogen cycle and may be pivotally important for N-limited ***,past models largely overlo oked the spatial and chemical inhomogeneity of atmospheric ONpand were thus deficient in assessing global *** constructed a comprehensive global model of atmospheric gaseous and particulate organic nitrogen（ON）,including the latest knowledge on emissions and secondary *** this model,we simulated global atmospheric ONpabundances consistent with *** estimated global atmospheric ON deposition was 26 Tg N yr-1,predominantly in the form of ONp(23 Tg N yr-1)and mostly from wildfires（37%）,oceans（22%） and aqueous productions（17%）.Globally,ONpcontributed as much as 40% to 80% of the total N deposition downwind of biomass-burning *** ONpdeposition thus constituted the dominant external N supply to the N-limited boreal forests,tundras and the Arctic Ocean,and its importance maybe amplified in a future warming climate.

关键词： organic nitrogen aerosol secondary organic nitrogen biomass burning

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