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32nd ACM International Conference on Multimedia, MM 2024

作者： Xi, Gongli Tian, Ye Yang, Mengyu Zhang, Lanshan Que, Xirong Wang, Wendong State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798400706868

Masked image modeling (MIM), as a self-supervised learning paradigm in computer vision, has gained widespread attention among researchers. MIM operates by training the model to predict masked patches of the image. Given the sparse nature of image semantics, it is imperative to devise a masking strategy that steers the model towards reconstructing high-semantic regions. However, conventional mask strategies often miss these high-semantic regions or lack alignment with the masks and semantics. To solve this, we propose the Global Patch-wise Attention (GPA) framework, a transferable and efficient framework for MIM pre-training. We observe that the attention between patches can be the metric of identifying high-semantic regions, which can guide the model to learn more effective representations. Therefore, we firstly define the global patch-wise attention via vision transformer blocks. Then we design the soft-to-hard mask generation to guide the model gradually focusing on high semantic regions identified by GPA (GPA as a teacher). Finally, we design an extra task to predict GPA (GPA as a feature). Experiments conducted under various settings demonstrate that our proposed GPA framework enables MIM to learn better representations, which benefit the model across a wide range of downstream tasks. Furthermore, our GPA framework can be easily and effectively transferred to various MIM architectures. © 2024 ACM.

关键词： Self-supervised learning

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Multivariate time-series anomaly detection

Multivariate time-series anomaly detection

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2023 International Conference on Intelligent Systems, Communications, and Computer networks, ISCCN 2023

作者： Wang, Qifa Shen, Qiwei State Key Laboratory Of Networking And Switching Technology China

ISBN: (纸本)9781510666238

Anomalies are rare items that differ significantly from the majority of the data and raise suspicion. Time series anomaly detection is of great significance in industrial applications, data mining and other fields. In this paper, we propose an autoencoder-based anomaly detection model. In the encoder part, the dependency relationship between different time series is mined through the graph attention network, the time domain data features are extracted through the GRU, and the frequency domain features are extracted through the convolutional neural network. The temporal data is reconstructed using a decoder consisting of a recurrent neural network in the encoder part. The residual between the reconstructed data and the original data is used to further judge anomalies. Data cleaning is performed in the preprocessing part to improve model performance. The effectiveness of our method is demonstrated on three publicly available datasets, and our method is found to outperform four other common anomaly detection methods. © 2023 SPIE. All rights reserved.

关键词： Anomaly detection

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Route Selection Policies in 5G Multiple-hop IAB networks at mmWave Band

Route Selection Policies in 5G Multiple-hop IAB Networks at ...

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2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022

作者： Yan, Shiying Xu, Xiaodong Han, Shujun State Key Laboratory of Network and Switching Technology Beijing China

ISBN: (数字)9781665480901

ISBN: (纸本)9781665480901

The multiple-hop integrated access and backhaul (IAB) is proposed by the third generation partnership project (3GPP), which enables ultra-dense base stations to transmit bypassing obstacles in urban buildings. Combined with the use of millimeter wave (mmWave) band, IAB is regarded as a costeffective solution to improve the system capacity and spectral efficiency. In this paper, we investigate the route selection policies to maximize the network capacity with considering the interference. Taking the use of beamforming and in-band full-duplex technologies, this paper formulates a route selection problem to maximize the system capacity. Furthermore, a novel loadbased bandwidth partition strategy is investigated to solve the band allocation problem. A Dueling Deep Q network based route selection algorithm is formulated to maximize the system capacity. The simulation results demonstrate that the proposed algorithm can increase the system capacity while improving the spectral efficiency, and it outperforms other algorithms. © 2022 IEEE.

关键词： Millimeter waves

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Artemis: Contour-Guided 3D Sensing and Localization With mmWave Radar for Infrastructure-Assisted Autonomous Vehicles

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IEEE Internet of Things Journal 2025年第12期12卷 20056-20070页

作者： Deng, Kaikai Xing, Ling Wu, Honghai Ma, Huahong Gao, Jianping Ling, Yue Henan University of Science and Technology School of Information Engineering Luoyang471023 China Henan University of Science and Technology College of Vehicle and Traffic Engineering Luoyang471023 China Beijing University of Posts and Telecommunications State Key Laboratory of Network and Switching Technology Beijing100876 China

Infrastructure-assisted autonomous driving has become a new paradigm that enables autonomous vehicles to fuse sensor data and improve driving safety, where a key enabling technology for achieving this vision is to real-time and accurate registering 3D mmWave radar point clouds between the infrastructure and the vehicle. To this end, we propose Artemis, a novel lightweight system capable of achieving real-time registration with decimeter-level localization. Artemis consists of three components: (i) a modal association-based salient object extraction component leverages the complementary advantages of cameras and radars to extract semantics and areas of salient objects for radar point clouds;(ii) a salient object shape construction component extracts the shape contour of salient objects based on their inherent geometries;(iii) a contour-guided 3D point cloud registration component combines two key strategies, keypoint matching strategy and early exit strategy, to quickly select keypoints and transformation directions for achieving accurate registration in real-time. We implement and evaluate Artemis with two multi-view datasets collected in the CARLA platform and campus. The experiment results show that Artemis achieves an average registration error of 0.33 m within 32.26 ms. © 2014 IEEE.

关键词： Autonomous vehicles

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Genuine Einstein-Podolsky-Rosen steering of generalized three-qubit states via unsharp measurements

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Chinese Physics B 2023年第4期32卷 215-225页

作者：陈玉玉郭奋卓魏士慧温巧燕 School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China Henan Key Laboratory of Network Cryptography Technology Zhengzhou 450001China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China CETC Cyberspace Security Technology Co. Ltd.Beijing 100041China

We aim to explore all possible scenarios of(1→2)(where one wing is untrusted and the others two wings are trusted)and(2→1)(where two wings are untrusted,and one wing is trusted)genuine tripartite Einstein-Podolsky-Rosen(EPR)*** generalized Greenberger-Horne-Zeilinger(GHZ)state is shared between three spatially separated parties,Alice,Bob and *** both(1→2)and(2→1),we discuss the untrusted party and trusted party performing a sequence of unsharp measurements,*** each scenario,we deduce an upper bound on the number of sequential observers who can demonstrate genuine EPR steering through the quantum violation of tripartite steering *** results show that the maximum number of observers for the generalized GHZ states can be the same with that of the maximally GHZ state in a certain range of state ***,both the sharpness parameters range and the state parameters range in the scenario of(1→2)steering are larger than those in the scenario of(2→1)steering.

关键词： quantum information quantum steering generalized Greenberger-Horne-Zeilinger(GHZ)state

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Two-Hop Delay-Aware Energy Efficiency Resource Allocation in Space-Air-Ground Integrated Smart Grid network

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Computers, Materials & Continua 2025年第5期83卷 2429-2447页

作者： Qinghai Ou Min Yang Jingcai Kong Yang Yang Beijing FibrLink Communications Co.Ltd. Beijing100071China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China

The lack of communication infrastructure in remote regions presents significant obstacles to gathering data from smart power sensors(SPSs)in smart grid *** such cases,a space-air-ground integrated network serves as an effective emergency *** study addresses the challenge of optimizing the energy efficiency of data transmission fromSPSs to low Earth orbit(LEO)satellites through unmanned aerial vehicles(UAVs),considering both effective capacity and fronthaul link capacity *** to the non-convex nature of the problem,the objective function is reformulated,and a delay-aware energy-efficient power allocation and UAV trajectory design(DEPATD)algorithm is proposed as a two-loop *** the inner loop remains non-convex,the block coordinate descent(BCD)method is employed to decompose it into three subproblems:power allocation for SPSs,power allocation for UAVs,and UAV trajectory *** first two subproblems are solved using the Lagrangian dual method,while the third is addressed with the successive convex approximation(SCA)*** iteratively solving these subproblems,an efficient algorithm is developed to resolve the inner loop *** results demonstrate that the energy efficiency of the proposed DEPATD algorithm improves by 4.02% compared to the benchmark algorithm when the maximum transmission power of the SPSs increases from 0.1 to 0.45W.

关键词： Energy efficiency effective capacity delay requirement power allocation smart grid space-air-ground integrated network

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RecStream: Graph-aware Stream Management for Concurrent Recommendation Model Online Serving 31

RecStream: Graph-aware Stream Management for Concurrent Reco...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Guo, Shuxi Qi, Qi Sun, Haifeng Liao, Jianxin Wang, Jingyu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798891761971

Recommendation Models (RMs) are crucial for predicting user preferences and enhancing personalized experiences on large-scale platforms. As the application of recommendation models grows, optimizing their online serving performance has become a significant challenge. However, current serving systems perform poorly under highly concurrent scenarios. To address this, we introduce RecStream, a system designed to optimize stream configurations based on model characteristics for handling high concurrency requests. We employ a hybrid Graph Neural network architecture to determine the best configurations for various RMs. Experimental results demonstrate that RecStream achieves significant performance improvements, reducing latency by up to 74%. ©2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Resource Awareness and Dynamic Load Balancing in Satellite-Ground Integrated networks 4

Resource Awareness and Dynamic Load Balancing in Satellite-G...

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4th International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2023

作者： Ji, Xiaoyuan Yao, Haipeng Gong, Yongkang State Key Laboratory of Networking and Switching Technology BUPT China

ISBN: (纸本)9781510666412

With the rapid development of mobile communications, many applications have covered industry, healthcare, education, transportation, etc. The traditional ground network has limited coverage range and service capacity, which makes it hard to meet the transmission requirements of the above applications. Satellite-ground integrated networks (SGINs) are introduced to improve data rate and enlarge the network capacity. However, the management strategy of communication resources among these heterogeneous nodes differs greatly. Software defined networking (SDN) simplifies network management via decoupling forward plane and control plane, which is beneficial to boosting the central management for SGINs. Based on SDN architecture, we propose perceptual load balancing to make forwarding decisions. Furthermore, we downscale the substrate network to reduce the communication overhead. Massive experiments validate that our proposed multiple resources-aware based dynamic load balancing strategy extends the average network service time for about 24%, while the network overhead of transmitting information is reduced by 80%. © 2023 SPIE.

关键词： Satellites

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Satellite-assisted 6G wide-area edge intelligence:dynamics-aware task offloading and resource allocation for remote IoT services

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Science China(Information Sciences) 2025年第2期68卷 248-268页

作者： Di ZHAO Rui DING Bin SONG State Key Laboratory of Integrated Services Networks Xidian University Hangzhou Institute of Technology Xidian University China Satellite Network Group Co. Ltd.

Future 6G networks will integrate non-terrestrial communication with mobile edge computing to enable wide-area edge intelligence, providing ubiquitous communication and computation services for everyone and everything. In this paper, we introduce the intelligent cloud-edge-device architecture into low Earth orbit(LEO) satellite-supported remote Internet of Things(IoT) networks to facilitate latency-sensitive and compute-intensive IoT applications. However, the dynamic spatio-temporal characteristics inherent in LEO satellite networks, such as the high volatility of task traffic and the high mobility of space nodes, pose severe challenges. For efficient task execution, we investigate the joint optimization of cross-region task offloading and cross-domain resource allocation, and innovatively propose a spatio-temporal attention-based proximal policy optimization(STA-PPO) algorithm. Specifically, the temporal attention-based actor network analyzes the timing dependencies of task arrival and makes time-variant decisions. Simultaneously, the spatial attention-based critic network captures the spatial variations of satellite motion and evaluates the topology-related value. We verify the effectiveness of the cloud-edge-device collaboration through extensive simulations. Numerical results demonstrate that the STA-PPO algorithm outperforms benchmarks, showing the lowest system delay and the highest link throughput.

关键词： 6G wide-area edge intelligence cross-region task offloading cross-domain resource allocation spatio-temporal attention proximal policy optimization

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Graph Attention Residual network Based Routing and Fault-Tolerant Scheduling Mechanism for Data Flow in Power Communication network

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Computers, Materials & Continua 2024年第10期81卷 1641-1665页

作者： Zhihong Lin Zeng Zeng Yituan Yu Yinlin Ren Xuesong Qiu Jinqian Chen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China State Grid Jiangsu Electric Power Co. Ltd.Nanjing210008China

For permanent faults(PF)in the power communication network(PCN),such as link interruptions,the timesensitive networking(TSN)relied on by PCN,typically employs spatial redundancy fault-tolerance methods to keep service stability and reliability,which often limits TSN scheduling performance in fault-free ideal *** this paper proposes a graph attention residual network-based routing and fault-tolerant scheduling mechanism(GRFS)for data flow in PCN,which specifically includes a communication system architecture for integrated terminals based on a cyclic queuing and forwarding(CQF)model and fault recovery method,which reduces the impact of faults by simplified scheduling configurations of CQF and fault-tolerance of prioritizing the rerouting of faulty time-sensitive(TS)flows;considering that PF leading to changes in network topology is more appropriately solved by doing routing and time slot injection decisions hop-by-hop,and that reasonable network load can reduce the damage caused by PF and reserve resources for the rerouting of faulty TS flows,an optimization model for joint routing and scheduling is constructed with scheduling success rate as the objective,and with traffic latency and network load as constraints;to catch changes in TSN topology and traffic load,a D3QN algorithm based on a multi-head graph attention residual network(MGAR)is designed to solve the problem model,where the MGAR based encoder reconstructs the TSN status into feature embedding vectors,and a dueling network decoder performs decoding tasks on the reconstructed feature embedding *** results show that GRFS outperforms heuristic fault-tolerance algorithms and other benchmark schemes by approximately 10%in routing and scheduling success rate in ideal states and 5%in rerouting and rescheduling success rate in fault states.

关键词： Time-sensitive network deep reinforcement learning graph attention network fault tolerance

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