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Thoughts on the development of novel network technology

Science China(Information Sciences) 2018年第10期61卷 144-154页

作者： Jiangxing WU National Digital Switching System Engineering and Technological R&D Center

In this paper, we explore potential innovations that could lead to breakthrough developments in Internet technologies. The deep integration of the Internet and economic society brings professionalized service capacity demand, while existing Internet infrastructure with its current technological systems still face a number of challenges, such as intelligence, diversification, personalization, robustness, and ***, we analyze the actual foundation of innovation and specify the basic technical features of a novel network. Then, we propose a fully dimensionally definable open architecture as the primary direction, and consider reshaping baseline technologies as a starting point and discuss the core operational mechanisms of the novel network based on such reshaped baseline technologies.

关键词： novel Internet technology open architecture full-dimensional definability diversified addressing and routing intelligence general robust control

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Communication Interruption Analysis for Air-water Wireless Optical Communication

Communication Interruption Analysis for Air-water Wireless O...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Chi Yang Fang Yang Department of Electronic Engineering Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing P. R. China Key Laboratory of Digital TV System of Guangdong Province and Shenzhen City Research Institute of Tsinghua University in Shenzhen Shenzhen P. R. China

In air-water wireless optical communication, the optical signal may be completely reflected at the sea surface, which will cause signal interruption and seriously affect communication quality. Therefore, this paper analyzes the signal interruption probability and duration caused by total reflection at different wind speeds and transmitter inclination angles. The bit error rate (BEr) of L-ary pulse position modulation (L-PPM) across sea surface under different L values is studied in an attempt to find a suitable modulation method to optimize the BEr of the system. The BEr optimization effect is apparent when the wind speed is low and L=6. However, the optimization effect of L-PPM on BEr decreases with the increase in wind speed.

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A Streaming-based Algorithm for Overlapping Community detection

A Streaming-based Algorithm for Overlapping Community Detect...

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International Conference on Computer and Communications (ICCC)

作者： Hui Li Fucai Chen Jianpeng Zhang National Digital Switching System Engineering & Technological R&D Center Information Engineering University Zhengzhou China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

Mining the overlapping community structure is a very important task in complex network analysis. With the development of social network and Internet of things, the scale of data is becoming larger and larger. Many existing algorithms can not deal with such a large-scale network. In order to improve the efficiency of community detection in large-scale networks, an overlapping community detection algorithm based on graph streaming is proposed. The algorithm processes the edges in the network in a streaming mode, processes only one edge at a time and each edge is processed only once and then discarded. The algorithm divides the nodes according to the degree of node, the contribution of node to the community, and the number of connected edges between communities before and after the node's moving. Experimental results on real-life networks show that our proposed approach can quickly discover overlapping community structures in large-scale networks with linear computational complexity.

关键词： Social networking (online) Image edge detection Internet of Things data mining detection algorithms Computational complexity Task analysis

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Ultrahigh-power all binder-free hybrid supercapacitors based on single-crystal hexagonal nanorods of molecular sieve VSB-5 hierarchical electrodes

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Journal of the Taiwan Institute of Chemical Engineers 2024年 154卷

作者： Yeh, Po-Hung Huang, Kai-Chen Mathankumar, Mahendran Wei, Sung-Yen Anuratha, Krishnan Shanmugam Kuo, Chun-Yi Su, Chia-Hung Lin, Jeng-Yu Hsieh, Chien-Kuo Department of Materials Engineering Center for Plasma and Thin Film Technologies Ming Chi University of Technology New Taipei City24301 Taiwan Department of Chemical and Materials Engineering Tunghai University Taichung City407224 Taiwan R&D Lab SulfurScience Technology Co. Ltd. New Taipei City24301 Taiwan Department of Chemical Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Department of Engineering and system science National Tsing Hua University Hsinchu300044 Taiwan

Background: Molecular sieve Versailles Santa Barbara-5 (VSB-5) is a highly porous nanomaterial for electrochemical supercapacitor. Methods: A facile hydrothermal method is used to directly synthesize VSB-5 nanorods onto the Nickel Foam (NF). Significant findings: In this work, one-dimensional single-crystal hydrogen nickel phosphate hydroxide hydrate (Ni20[(OH)12(H2O)6][(HPO4)8(PO4)4]·12H2O, also denotes as VSB-5, hexagonal nanorods arrays are successfully synthesized on NF via a hydrothermal method, and applied them as positive electrodes for hybrid supercapacitor (HSC). The resultant open framework of VSB-5 with unique nanochannels provides the synchronous advantages of a large surface area with numerous active sites for enhancing faradic redox reactions and abundant pathways for promoting electrolyte ions diffusion, thus leading to excellent energy storage behavior. Furthermore, the HSC is fabricated by paring the direct growth of carbon nanotubes (CNTs) on NF as the electrical-double-layer-capacitor negative electrode. Both the VSB-5/NF and CNTs/NF electrodes are binder-free hierarchical structures, owning the lowest interfacial resistivities between active materials and current collects, avoiding the aggregation issues to allow the facile diffusion of electrolyte for maximally utilizing the surface area. The resultant all binder-free VSB-5/NF//CNTs/NF HSC shows remarkable electrochemical performance, which delivers a maximum energy density of 46.9 W h kg−1 at a power density of 1225 W kg−1 with excellent capacity retention of 98.18% after 10,000 cycles. © 2023

关键词： Molecular sieves

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Formal analysis and verification of industrial control system security via timed automata

Formal analysis and verification of industrial control syste...

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2020 International Conference on Internet of Things and Intelligent Applications, ITIA 2020

作者： Wang, Guoqing Zhuang, Lei Liu, Taotao Li, Shuxia Yang, Sijin Lan, Julong Zhengzhou University Advanced Network and High Reliabl Software Laboratory Zhengzhou China Zhengzhou University School of Information Engineering Zhengzhou China China National Digital Switching System Engineering and Technological R and Center Zhengzhou China

ISBN: (纸本)9781728193014

The industrial Internet of Things (IIoT) can facilitate industrial upgrading, intelligent manufacturing, and lean production. Industrial control system (ICS) is a vital support mechanism for many key infrastructures in the IIoT. However, natural defects in the ICS network security mechanism and the susceptibility of the programmable logic controller (PLC) program to malicious attack pose a threat to the safety of national infrastructure equipment. To improve the security of the underlying equipment in ICS, a model checking method based on timed automata is proposed in this work, which can effectively model the control process and accurately simulate the system state when incorporating time factors. Formal analysis of the ICS and PLC is then conducted to formulate malware detection rules which can constrain the normal behavior of the system. The model checking tool UPPAAL is then used to verify the properties by detecting whether there is an exception in the system and determine the behavior of malware through counter-examples. The chemical reaction control system in Tennessee-Eastman process is taken as an example to carry out modeling, characterization, and verification, and can effectively detect multiple patterns of malware and propose relevant security policy recommendations. © 2020 IEEE.

关键词： Model checking

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Cloud-magnetic resonance imaging system:In the era of 6G and artificial intelligence

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Magnetic resonance Letters 2025年第1期5卷 52-63页

作者： Yirong Zhou Yanhuang Wu Yuhan Su Jing Li Jianyu Cai Yongfu You Jianjun Zhou di Guo Xiaobo Qu Department of Electronic Science Intelligent Medical Imaging R&D CenterFujian Provincial Key Laboratory of Plasma and Magnetic ResonanceNational Institute for Data Science in Health and MedicineXiamen UniversityXiamen361104China Department of Electronic Science Key Laboratory of Digital Fujian on IoT CommunicationXiamen UniversityXiamen361104China Shanghai Electric Group Co. LtdShanghai200002China China Telecom Group Quanzhou362018China China Mobile Group Xiamen361009China Department of Radiology Zhongshan Hospital(Xiamen)Fudan UniversityXiamen Municipal Clinical Research Center for Medical ImagingFujian Province Key Clinical Specialty Construction Project(Medical Imaging Department)Xiamen Key Laboratory of Clinical Transformation of Imaging Big Data and Artificial IntelligenceXiamen361006China School of Computer and Information Engineering Xiamen University of TechnologyXiamen361024China

Magnetic resonance imaging(MrI)plays an important role in medical diagnosis,generating petabytes of image data annually in large *** voluminous data stream requires a significant amount of network bandwidth and extensive storage ***,local data processing demands substantial manpower and hardware *** isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and *** this work,we anticipate an innovative MrI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain *** system is called Cloud-MrI,aiming at solving the problems of MrI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative *** workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic resonance in Medicine raw data(ISMrMrd)***,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic ***,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other *** Cloud-MrI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.

关键词： Magnetic resonance imaging Cloud computing 6G bandwidth Artificial intelligence Edge computing Federated learning Blockchain

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MdLB:a metadata dynamic load balancing mechanism based on reinforcement learning

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Frontiers of Information technology & Electronic engineering 2020年第9期21卷 1034-1046页

作者： Zhao-qi WU Jin WEI Fan ZHANG Wei GUO Guang-wei XIE National Digital Switching System Engineering&Technological R&D Center Zhengzhou 450002China School of Computer Science Fudan UniversityShanghai 200433China Data Arena Institute Fudan UniversityShanghai 200433China

With the growing amount of information and data, object-oriented storage systems have been widely used in many applications, including the Google File system, Amazon S3, Hadoop distributed File system, and Ceph, in which load balancing of metadata plays an important role in improving the input/output performance of the entire system. Unbalanced load on the metadata server leads to a serious bottleneck problem for system performance. However, most existing metadata load balancing strategies, which are based on subtree segmentation or hashing, lack good dynamics and adaptability. In this study, we propose a metadata dynamic load balancing(MdLB) mechanism based on reinforcement learning(rL). We learn that the Q_learning algorithm and our rL-based strategy consist of three modules, i.e., the policy selection network, load balancing network, and parameter update network. Experimental results show that the proposed MdLB algorithm can adjust the load dynamically according to the performance of the metadata servers, and that it has good adaptability in the case of sudden change of data volume.

关键词： Object-oriented storage system Metadata dynamic load balancing reinforcement learning Q_learning

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Effect of Interdiffusion Layer of Functionally Graded Al–Cu Composites Fabricated by Spark Plasma Sintering on Mechanical and Thermal Properties

SSRN

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SSrN 2024年

作者： Kim, dasom Lee, Yoonseok Kim, Kyungju Kwon, Hansang Department of Materials System Engineering Pukyong National University Busan48547 Korea Republic of Pukyong National University Industry-University Cooperation Foundation Busan48547 Korea Republic of Industrial Science Technology Research Center Pukyong National University Busan48547 Korea Republic of Department of R&D Next Generation Materials Co. Ltd. Busan48547 Korea Republic of

The effect of the microstructure of multi-layer Al–Cu functionally graded materials (FGMs) fabricated through spark plasma sintering (SPS) on the mechanical and thermal properties was systemically investigated. Uniformly mixed Al–25, 50, 75 Cu (vol%) powder samples were prepared by mechanical ball milling and used for fabricating two types of FGMs: FGM 1 with three layers (Cu/Al–50Cu/Al) and FGM 2 with five layers (Cu/Al–75Cu/Al–50Cu/Al–25Cu/Al). These FGMs were then sintering at 400 °C under a compressive pressure of 250 MPa for 5 min. The microstructures of the sintered FGMs exhibited gradual variations in the Al and Cu contents. An interdiffusion layer composed of Cu9Al4 and CuAl2 at the layer/layer interfaces was observed, the thickness of which was analyzed by energy-dispersive spectroscopy line mapping. Subsequently, the hardness and thermal conductivity of FGM 1 and FGM 2 were compared with those of Al, Al–25Cu, Al–50Cu, Al–75Cu, and Cu samples individually sintered under the same conditions, and the effect of the microstructures on the mechanical and thermal properties of the materials were discussed. © 2024, The Authors. All rights reserved.

关键词： Functionally graded materials

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MdSA: Security scheduling mechanism for a reliable SdN control layer based on mimic defense

MDSA: Security scheduling mechanism for a reliable SDN contr...

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International Conference on Intelligent Computing, Communication and devices, ICCd 2017

作者： Zeyu, Gu Xingming, Zhang Qing, Mu National Digital Switching System Engineering & Technological R&D Center Zhengzhou China National Defense University Beijing China

ISBN: (纸本)9789811089435

Aiming at the single-point vulnerability such as tampering attack of SdN controllers, current solutions have passive defense defects and cannot solve the security problem of control layer fundamentally. Combined with state-of-the-art moving target defense, cyber mimic defense, and other active defense technologies, we present a security scheduling mechanism with heterogeneous redundant structure, which provides system dynamics and diversity for improved security. We also consider the load factor while designing the scheduling algorithm in our model, thus transforming it into a dynamic optimization problem. Several solutions are compared in terms of anti-attack capability, and simulation results show that proactive scheduling strategies can obviously improve system security as dynamic and diversity properties block the adversary’s attack process. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Scheduling algorithms

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A Novel Preprocessing Methodology for dNN-Based Intrusion detection

A Novel Preprocessing Methodology for DNN-Based Intrusion De...

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International Conference on Computer and Communications (ICCC)

作者： Peng Chen Yunfei Guo Jianpeng Zhang Yawen Wang Hongchao Hu Information Engineering University Zhengzhou China National Digital Switching System Engineering & Technological R&D Center Zhengzhou China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

Intrusion detection system (IdS) plays a vital role in cybersecurity. One major challenge in state-of-the-art IdS is that the Advanced Persistent Threats (APTs) cannot be well detected. deep Neural Networks (dNNs) extract latent features of input data, which is considered to be able to capture intrinsic property of APTs, to detect APTs. However, dNN is not well used in APT detection. In this paper, a dNN model is utilized for intrusion detection and a novel method of preprocessing is proposed to improve the performance of the detection algorithms. We consider the statistical characteristics of training set to be the statistical characteristics of test set and detection set. Experiment results show that our preprocessing methodology achieves a better performance in terms of accuracy, recall and F1 Score than traditional preprocessing methods, which means a better detection for APTs.

关键词： Training Machine learning algorithms Neural networks Intrusion detection Feature extraction Throughput real-time systems

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