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23rd International Conference on Extending Database Technology, EDBT 2020

作者： Yang, Di Li, Hui Wang, Meng Li, Dan Cui, Jiangtao School of Cyber Engineering State Key Laboratory of Integrated Services Networks Xidian University Xi’an China School of Computer Science Xi’an Polytechnic University Xi’an China School of Computer Science and Technology Xidian University Xi’an China

ISBN: (纸本)9783893180837

Facility placement has been receiving considerable research attention due to the proliferation of GPS equipped mobile devices. Establishing new facilities has a wide spectrum of applications including billboard placement, wildlife monitoring, supermarket/restaurant placement, etc. In all these applications, finding the best position to place a facility can lead to the optimal benefit given plenty of target users, which are associated with many historical position logs, e.g., user check-in data, wildlife monitor logs. In this work, we demonstrate a general system, namely MALOS, for answering the majority of facility placement problems given movement logs of a series of target users. Specifically, MALOS leverages on three academic works in the following scenarios. Find the best one/k position/s to place one/k new facilities in order that the overall benefit can be maximized;find one position to place an extra facility given that there are k existing facilities in different places, such that the overall benefit can be maximized. Notably, in MALOS we consider only the geographical issues that are common in all facility placement applications and choose not to take into account the specialized factors that vary across applications, such as billboard size, restaurant type, etc. We shall provide an opportunity for demonstration users to experience all kinds of these facility placement queries with a real-world historical movement logs and corresponding maps interface. © 2020 Copyright held by the owner/author(s).

关键词： Animals

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Data center network acquisition symptom algorithm based on Hamiltonian Cycle

Data center network acquisition symptom algorithm based on H...

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

作者： Du, Xiaoyu Zhao, Zhiyu Han, Zhijie Wang, Bo School of Computer and Information Engineering Henan University International Joint Research Laboratory for Cooperative Vehicular Networks of Henan Kaifeng Henan China School of Computer and Information Engineering Henan University Kaifeng Henan China Lucky Huaguang Graphics CO. Ltd Henan China

ISBN: (纸本)9781450387828

In the network, fault diagnosis includes two major phases: first the test result (symptom) is obtained through the test model;and second, the faulty node is determined by applying a diagnosis algorithm to the symptoms. In this paper, we mainly study the first stage, and an efficient algorithm based on Hamiltonian cycle - -ASHC (acquiring symptom based on Hamiltonian cycle) is proposed, which mainly sends test data packets via Hamilton cycle to test each server and record the test results, then we use simple comparison models for test results to obtain test symptoms. The advantage of this algorithm is that the central server does not need to communicate with each server directly, so as to save system resources. © 2020 ACM.

关键词： Failure analysis

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Risk Modeling and Traceability of Boundary Attacks on Internet of Power Systems Based on Complex networks

Risk Modeling and Traceability of Boundary Attacks on Intern...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Xin Li Zhaoyang Qu Tong Yu Ming Xie Fu Yu Wei Ding School of Electrical Engineering Northeast Electric Power University Jilin China People’s Bank of China Qinghai Provincial Branch Xining China China Southern Power Grid Guangxi Power Grid Co. Ltd. Research Institute Nanning China Bijie Power Supply Bureau China Guizhou Power Grid Co. Ltd. Bijie China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

With the increasing intelligence of power IoT terminal devices, the massive volume of data transmission, and the widespread adoption of shared services, traditional terminal boundary security mechanisms are unable to keep up with the rapid development of network technologies and applications. Additionally, they fail to trace and source network attacks, leading to frequent organized and purposeful malicious attack incidents. To address these issues, this paper proposes a research method for risk modeling and traceability of boundary attacks on power IoT terminals based on complex networks. First, based on the node information of power IoT terminal devices and complex network theory, a terminal boundary attack network (TBAN) is established. Next, using indicators related to complex network theory, such as degree, in-degree, and out-degree, the terminal boundary attack network is analyzed. Furthermore, a staged TBAN is proposed to analyze the attack risks at different times. Then, combining causal theory, a method for tracing and sourcing terminal boundary attacks based on a causal Bayesian network is proposed to identify and trace malicious attacks. Finally, validation and testing analysis are conducted using the actual deployment of power IoT terminal devices. The proposed analysis method transforms the spatial characteristics of the power IoT terminal boundary into a temporally sequential TBAN, which not only visually reflects attack risks but also reveals the temporal relationships of terminal boundary attacks between lines.

关键词： Complex networks Transforms Data science Data models Bayes methods Power systems Internet Security Data communication Testing

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Nanoseconds CDR Enabled by Clock Distribution and Protection Sequence Insertion in Optical

Nanoseconds CDR Enabled by Clock Distribution and Protection...

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OptoElectronics and Communications Conference, OECC

作者： Yisong Zhao Changsheng Yang Daohang Dang Yuanzhi Guo Shikui Shen Ran Wen Bin Chen Bingli Guo Chuanchuan Yang Nan Hua Xuwei Xue Shanguo Huang State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing China China Unicom Research Institute Beijing China School of Computer Science and Information Engineering Hefei University of Technology Hefei China The State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing China

The scheme combining clock distribution and protection sequence insertion from the network perspective is proposed and experimentally investigated to implement a 3.1 nanoseconds clock and data recovery in optical swit...

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Adaptive beamforming for optical wireless communication via fiber modal control

arXiv

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arXiv 2023年

作者： Li, Chao Zhang, Yiwen Yan, Xinda Wang, Yuzhe Zhang, Xuebing Cui, Jian Zhu, Lei Li, Juhao Li, Zilun Yu, Shaohua Cao, Zizheng Koonen, A.M.J. Hsu, Chia Wei Peng Cheng Laboratory Guangdong Shenzhen518055 China Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States Institute for Photonic Integration Department of Electrical Engineering Eindhoven University of Technology Eindhoven5612 AZ Netherlands State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing100871 China Division of Vascular Surgery The First Affiliated Hospital Sun Yat-sen University Guangdong Guangzhou510080 China

High-speed optical wireless communication can address the exponential growth in data traffic. Adaptive beamforming customized for the target location is crucial, but existing solutions such as liquidcrystal spatial light modulators and microelectromechanical systems require costly micro/nano manufacturing, delicate alignment, and a high degree of mechanical stability. These challenges reflect the fragility of integrating a fiber network with micro/nano mechanical or photonic systems. Here, we realize low-cost, low-loss, and fiber-compatible beamforming and continuous beam steering through controlled bending of a multi-mode fiber that modifies its modal coupling, and use it to enable flexible optical wireless communication at 10 Gb/s. By using the fiber modal coupling as degrees of freedom rather than an impediment, this approach offers a promising solution for flexible and cost-effective optical wireless communication networks. © 2023, CC BY-NC-SA.

关键词： Fibers

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Joint User Association and Transmission Scheduling in Integrated mmWave Access and Terahertz Backhaul networks

arXiv

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arXiv 2023年

作者： Wang, Lei Ai, Bo Niu, Yong Jiang, Haiyan Mao, Shiwen Zhong, Zhangdui Wang, Ning The State Key Laboratory of Advanced Rail Autonomous Operation The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China The State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing100044 China The Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China The Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The School of Information Engineering Zhengzhou University Zhengzhou450001 China

Terahertz wireless backhaul is expected to meet the high-speed backhaul requirements of future ultra-dense networks using millimeter-wave (mmWave) base stations (BSs). In order to achieve higher network capacity with limited resources and meet the quality of service (QoS) requirements of more users in the integrated mmWave access and terahertz backhaul network, this paper formulates a problem of maximizing the number of users successfully served in both the access and backhaul links. Since the problem is a non-linear integer optimization problem, a minimum rate ratio user association and transmission scheduling algorithm is proposed to obtain a suboptimal solution. The proposed algorithm takes the minimum rate ratio as the user association criterion and schedules first the users with fewer backhaul transmission slots. In addition, the algorithm will update the number of access transmission slots allocated to users and the access scheduling results after the backhaul scheduling phase. Numerical results show that the proposed algorithm outperforms several benchmark algorithms in terms of the number of served users and system throughput, and it can cope with a large number of bursty user requests. Copyright © 2023, The Authors. All rights reserved.

关键词： Millimeter waves

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TraCemop: Towards Federated Learning with Traceable Contribution Evaluation and Model Ownership Protection

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IEEE Transactions on Mobile Computing 2025年

作者： Liu, Jingwei Zhou, Zihan Sun, Rong Liu, Lei Lu, Rongxing Dustdar, Schahram Niyato, Dusit Ministry of Education Engineering Research Center of Blockchain Technology Application and Evaluation China Xidian University Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'an710071 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China Xidian University Guangzhou Institute of Technology Guangzhou510555 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Queen's University School of Computing KingstonONK7L 2N8 Canada TU Wien Distributed Systems Group Austria UPF ICREA Barcelona Spain Nanyang Technological University School of Computer Science and Engineering Singapore

Federated Learning (FL) allows multiple clients to collaboratively train machine learning models without the need to share their local private data. As a result, it can effectively address the issue of data fragmentation. Nevertheless, insufficient evaluation of individual contributions and the lack of protections for both the intellectual property rights (IPR) of models and client privacy can greatly reduce clients' motivations in federated training. To address these challenges, this paper introduces the Traceable Contribution Evaluation and Model Ownership Protection (TraCemop) framework for federated learning, which allows each client to swiftly assess the contributions of others in each round, with integrated support for the traceability of evaluation results. To safeguard the intellectual property of models, a collective watermark is embedded in the global model. Additionally, a secure mechanism for verifying model ownership is also available in case of disputes. Security analysis indicates that TraCemop is capable of resisting data reconstruction attacks as well as various types of model copyright infringements. Finally, we evaluate the proposed framework using two commonly-used datasets, and the experimental results show a significant improvement in the efficiency of contribution evaluation compared to existing methods. Meanwhile, IPR infringement tests on TraCemop reveal that the proposed framework is resilient against malicious efforts to monopolize model ownership. © 2002-2012 IEEE.

关键词： Federated learning

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A Low-Fabrication-Temperature Erbium-Based Waveguide Amplifier

A Low-Fabrication-Temperature Erbium-Based Waveguide Amplifi...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Bo Wang Xingjun Wang Department of Electronics School of Electronics Engineering and Computer Science State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China Frontier Science Center for Nano-Optoelectronics Peking University Beijing China Peking University Yangtze Delta Institute of Optoelectronics Nantong China Peng Cheng Laboratory Shenzhen China

In recent years, with the continuous development of silicon photonics technology, more and more optoelectronic devices have integrated into silicon-base platform. However, the inter-device transmission and coupling loss is serious, which results in an urgent need for on-chip waveguide amplifiers to compensate for the loss. Erbium silicate is an ideal gain material because of its extremely high Er 3+ concentration (10 22 cm −3 ). Nevertheless, Erbium silicate must be annealed above 1000 °C to activate the Er 3+ , which would damage other on-chip optoelectronic components. To solve this problem, here, we report a low-fabrication-temperature erbium-based waveguide amplifier. Erbium-ytterbium silicate and Bi 2 O 3 mixed film is used as gain material, which can activate the Er 3+ at 600 °C annealing condition. The waveguide amplifier was fabricated by lift-off process due to that the mixed film is hard to etch. Finally, 2 dB signal enhancement has been observed at 1550nm. This work shows that the proposed material has great potential for on-chip waveguide amplifier.

关键词： Optical fiber amplifiers Optical losses Annealing Stimulated emission Erbium-doped fiber amplifiers Propagation losses System-on-chip

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Network Data-Knowledge Engine: Supporting 6G Endogenous Intelligence with Digital Twin

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IEEE Network 2025年

作者： Wang, Dan Zhu, Keke Song, Bin Du, Xiaojiang Xidian University State Key Laboratory of Integrated Services Networks 710071 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

With the rapid development of 5G cellular systems, both industry and academia are focusing on exploring 6G communication, especially supported by artificial intelligence (AI), which has spurred heated discussions on the convergence of AI technologies and future wireless communications. It is envisioned that 6G will rely heavily on AI to enable data-driven and knowledge-driven solutions in large-scale heterogeneous networks, thereby realizing endogenous intelligence in 6G. To achieve this, digital twin (DT) technology can serve as a powerful enabler for unlocking the full potential of future 6G networks. In this paper, we introduce a six-dimensional framework of the digital twin to support endogenous intelligence in 6G through the integration of AI technology and DT. We propose a self-adaptive hierarchical digital twin network (SAHDTN) based on the above DT framework to achieve self-optimization for the 6G network. Furthermore, we incorporate several key technologies to support endogenous intelligence, including a network data-knowledge engine powered by collective reinforcement learning, transfer learning, and knowledge graphs. © 1986-2012 IEEE.

关键词： Transfer learning

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Density-aware and Depth-aware Visual Representation for Zero-Shot Object Counting

Density-aware and Depth-aware Visual Representation for Zero...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Fang Nan Feng Tian Ni Zhang Nian Liu Haonan Miao Guang Dai Mengmeng Wang Faculty of Electronic and Information Engineering Xi’an Jiaotong University Xi’an China Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an China School of Automation Northwestern Polytechnical University Xi’an China Computer Vision Department Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi UAE SGIT AI Lab State Grid Corporation of China Zhejiang University of Technology Hang Zhou China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Previous methods often utilize CLIP semantic classifiers with class names for zero-shot object counting. However, they ignore crucial density and depth knowledge for counting tasks. Thus, we propose a density-aware and depth-aware prompt counting model, which captures density information via learning density-aware prompts based on density-aware contrastive loss and incorporates depth guidance with predefined depth-aware prompts. To facilitate the training process, we design two strategies for standard counting loss and the contrastive loss, where the former prioritizes larger and sparser objects initially, gradually focusing on smaller and denser objects, and the latter adopts coarse-to-fine density learning. Besides, we construct a dataset named LVIS-372 with more real-world scenarios and balanced instance distribution compared to existing ones. Finally, the experimental results demonstrate the effectiveness of our proposed method.

关键词： Training Visualization Semantics Focusing Signal processing Acoustics Power capacitors Speech processing Standards

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