检索结果-内蒙古大学图书馆

Semi-Federated Learning for Connected Intelligence With Computing-Heterogeneous Devices

IEEE INTERNET OF THINGS JOURNAL 2024年第21期11卷 34078-34092页

作者： Han, Jiachen Ni, Wanli Li, Li Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Lab Adv Informat Networks Beijing 100876 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

Federated learning (FL) is a promising distributed learning approach which enables multiple devices to collaboratively train deep neural networks in a privacy-preserving fashion. However, computing-limited devices in Internet of Things (IoT) networks are difficult to perform local model training, which is an obstacle to implementing connected intelligence at the network edge. In this article, we propose a semi-federated learning (SemiFL) framework to support computing-heterogeneous devices for collaborative model training, even if some local devices do not have computing capabilities. Specifically, in SemiFL, computing-limited devices upload raw data to the base station (BS), while computing-powerful devices upload model parameters to the BS. To characterize the achievable learning performance of SemiFL in practical IoT networks, we derive the convergence upper bound with nonindependent and identically distributed (non-IID) data. Furthermore, we formulate an optimization problem to minimize the computation and communication latency by jointly design the transmit power of IoT devices and the receive factor at the BS. Accordingly, we propose an two-stage optimization algorithm to solve the formulated nonconvex problem efficiently. Extensive simulation results show that our SemiFL framework outperforms traditional FL in both IID and non-IID settings. In addition, it is shown that the proposed algorithm achieves lower latency than benchmarks under different settings.

关键词： Computational modeling Atmospheric modeling Performance evaluation Internet of Things Training Data models Convergence Connected intelligence convergence analysis heterogeneous devices latency minimization over-the-air computation (AirComp) semi-federated learning (SemiFL)

来源：评论

学校读者我要写书评

暂无评论

CEL: Cost-Aware Edge-Assisted Livecast via Optimization With Shapley Value

引用

IEEE INTERNET OF THINGS JOURNAL 2024年第5期11卷 7805-7816页

作者： Wang, Yizong Zhao, Dong Guo, Zixuan Gao, Teng Ma, Huadong Du, Yang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci Beijing 100876 Peoples R China

The increasingly prevalent livecast streaming causes expensive bandwidth costs and delivery capacity challenges for the content delivery network (CDN) service. As an emerging paradigm, edge computing offers new opportunities to address this issue. The existing works are limited to the data volume pricing model. In contrast, we focus on the 95th-percentile pricing model, which is adopted by many large-scale livecast systems. We propose a Cost-aware Edge-assisted Livecast system (CEL) to minimize the bandwidth cost, consisting of two components: 1) the Shapley values are leveraged to model the actual bandwidth costs for the CDN and edge servers in different time slots, together with acceleration technologies for fast Shapley value estimation and 2) a greedy request scheduling algorithm with theoretical guarantees is proposed to solve the online request scheduling problem, which is NP-hard. Based on real-world data from an operational livecast system, our experiments demonstrate that CEL is time-efficient and achieves at least 14.81% bandwidth cost savings compared with four state-of-the-art methods.

关键词： 95th-percentile pricing model content delivery network (CDN) edge computing livecast system Shapley value

来源：评论

学校读者我要写书评

暂无评论

Bandwidth-Efficient Mobile Volumetric Video Streaming by Exploiting Inter-Frame Correlation

引用

IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第10期23卷 9410-9423页

作者： Wang, Yizong Zhao, Dong Zhang, Huanhuan Gao, Teng Guo, Zixuan Huang, Chenghao Ma, Huadong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci Beijing 100876 Peoples R China

Volumetric videos offer viewers more immersive experiences, enabling a variety of applications. However, state-of-the-art streaming systems still need hundreds of Mbps bandwidth to transmit volumetric videos, exceeding the common bandwidth capabilities of mobile devices. We find a research gap in reusing inter-frame redundant information to reduce bandwidth consumption, while the existing inter-frame compression methods rely on the so-called explicit correlation, i.e., the redundancy from the same/adjacent locations in the previous frame, which does not apply to highly dynamic frames or dynamic viewports. This paper introduces a new concept called implicit correlation, i.e., the consistency of topological structures, which stably exists in dynamic frames and is beneficial for reducing bandwidth consumption. We design a mobile volumetric video streaming system Hermes consisting of an implicit correlation encoder to reduce bandwidth consumption and a hybrid streaming method that adapts to dynamic viewports. Experiments on public datasets show that Hermes achieves a frame rate of 30+ FPS over daily networks and on commodity smartphones, with at least 3.64x and 3.34x improvement compared with two state-of-the-art baselines, respectively.

关键词： Streaming media Correlation Bandwidth Point cloud compression Entropy Encoding Redundancy Volumetric video streaming entropy encoding implicit correlation

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Multiple Access Scheme with Power Control for mMTC Networks 23

Energy-Efficient Multiple Access Scheme with Power Control f...

引用

23rd IEEE International Conference on Communication technology, ICCT 2023

作者： Meng, Yue Peng, keyi Wu, Di Zhang, Zhi Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China

ISBN: (纸本)9798350325959

The grant-free non-orthogonal multiple access (GF-NOMA) is especially conducive to support massive machine-type communication (mMTC) service. Owing to the limited energy resources and the reliability requirements for MTC devices, how to design an energy-efficient multiple access scheme is an urgent problem. In this paper, we investigate a comprehensive learning framework for GF-NOMA with power control scheme in mMTC networks, focusing on the power level design and the collision resolution. We formulate an optimization problem aiming to minimize the long-term system power consumption with satisfying the constraint of packet error rate. A scheme based on a deep reinforcement learning approach is further applied, comprising two interrelated subalgorithm, to optimize the power levels and the contention-transmission unit (CTU) allocation. The numerical results demonstrate the superiority of our proposed scheme over other resource allocation schemes, particularly in terms of enhancing the network energy efficiency. © 2023 IEEE.

关键词： deep reinforcement learning energy-efficient GF-NOMA multiple access Power control

来源：评论

学校读者我要写书评

暂无评论

PsyQoE: Improving Quality-of-Experience Assessment With Psychological Effects in Video Streaming

引用

IEEE TRANSACTIONS ON SERVICES COMPUTING 2024年第6期17卷 4138-4150页

作者： Sheng, Daoxu Qi, Qi Wang, Jingyu Li, Lianyuan Yu, Wei Liao, Jianxin Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China China Mobile Res Inst Dept Serv Technol Beijing 100053 Peoples R China

As media streaming grows, service providers have to focus more on users' quality of experience (QoE). Among the metrics that influence QoE, network-oriented and media-oriented factors have been the primary concern of most existing work. Apart from the two factors, however, another crucial aspect of QoE is the user. Though the analysis and modeling of users is a turning point in the transition from QoS to QoE, the impact of users' memory and cognitive-psychological effects have not been fully explored. In this work, we analyze, validate and quantify the relationship between multiple cognitive effects and the QoE of users in media streaming. We propose PsyQoE, a new QoE assessment framework that uniquely focuses on user perceptions during media sessions. Besides providing real-time QoE assessments through leveraging machine learning, PsyQoE also predicts the overall QoE by taking into account user biases and long-term effects. Additionally, we have designed a further modified version to cater to the needs of hardware and energy-restricted scenarios. When compared with other existing methods, our approach demonstrates enhanced performance by boosting accuracy by 7% to 16%. It also provides better interpretability and broader applicability.

关键词： Quality of experience Streaming media Psychology Media Bit rate Quality of service Real-time systems Multimedia adaptive video streaming quality-of-experience assessment

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Reinforcement Learning With Attention Reward 22

Hierarchical Reinforcement Learning With Attention Reward

引用

22nd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023

作者： Luo, Sihong Chen, Jinghao Hu, Zheng Zhang, Chunhong Zhuang, Benhui State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

Hierarchical Reinforcement Learning (HRL) is a promising approach for complex tasks with greater sample efficiency because it can break a task into sets of short subtasks and provide a denser subgoal-related intrinsic reward, making credit assignments less challenging. However, none of the conventional subgoal-related intrinsic rewards utilize task-specified knowledge, which limits the sample efficiency of these HRL methods. We propose Hierarchical Reinforcement Learning with Attention Reward (HiAR) that motivates agents to focus on the part of the environment controlled by their actions. We introduce a measure of the control over each dimension in the state space and discuss how we integrated it into the HRL method to improve the sample efficiency. © 2023 International Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

A Collaborative Allocation Algorithm of Communicating, Caching and Computing Resources in Local Power Wireless Communication Network

引用

INFORMATION 2024年第6期15卷 309页

作者： Tang, Jiajia Shao, Sujie Guo, Shaoyong Wang, Ye Wu, Shuang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China State Grid Ningxia Elect Power Co Ltd Yinchuan 750001 Peoples R China

With the rapid development of new power systems, diverse new power services have imposed stricter requirements on network resources and performance. However, the traditional method of transmitting request data to the IoT management platform for unified processing suffers from large delays due to long transmission distances, making it difficult to meet the delay requirements of new power services. Therefore, to reduce the transmission delay, data transmission, storage and computation need to be performed locally. However, due to the limited resources of individual nodes in the local power wireless communication network, issues such as tight coupling between devices and resources and a lack of flexible allocation need to be addressed. The collaborative allocation of resources among multiple nodes in the local network is necessary to satisfy the multi-dimensional resource requirements of new power services. In response to the problems of limited node resources, inflexible resource allocation, and the high complexity of multi-dimensional resource allocation in local power wireless communication networks, this paper proposes a multi-objective joint optimization model for the collaborative allocation of communication, storage, and computing resources. This model utilizes the computational characteristics of communication resources to reduce the dimensionality of the objective function. Furthermore, a mouse swarm optimization algorithm based on multi-strategy improvements is proposed. The simulation results demonstrate that this method can effectively reduce the total system delay and improve the utilization of network resources.

关键词： resource allocation RSO new power system differential evolution

来源：评论

学校读者我要写书评

暂无评论

MS-Transformer: Masked and Sparse Transformer for Point Cloud Registration

MS-Transformer: Masked and Sparse Transformer for Point Clou...

引用

2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Jia, Qingyuan Luo, Guiyang Yuan, Quan Li, Jinglin Shao, Congzhang Chen, Ziyue Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China

ISBN: (纸本)9798350337020

In this paper, we propose a masked and sparse transformer to address the problem of point cloud registration with low overlap. The mask mechanism reduces the overall data, increasing the corresponding point ratio in the overlap region, while also reducing the computational cost to accelerate the algorithm's execution speed. Moreover, we combine spatial position encoding and sparse self-attention to establish relationships within the source point cloud, as well as the relationships and attention scores between the source and target point clouds. This approach is specifically designed for the task of point cloud registration. Finally, we search for the maximum overlap area by matching the spatial consistency between points and calculate the 3D transformation matrix to complete the registration process. Our method achieves an improvement in the inlier ratio and performs well on the 3DMatch and 3DLoMatch datasets, demonstrating high registration efficiency. © 2023 IEEE.

关键词： Mask mechanism Point cloud registration Self-attention

来源：评论

学校读者我要写书评

暂无评论

A Quantum-Resistant Lightweight Hierarchical Privacy Protection Scheme for Traffic Images

引用

IEEE Internet of Things Journal 2025年第13期12卷 24615-24630页

作者： Qi, Yuning Bi, Jingguo Li, Lixiang Peng, Haipeng Zhang, Ran He, Xiaofei Beijing University of Posts and Telecommunications School of Cyberspace Security Beijing100876 China Beijing University of Posts and Telecommunications Information Security Center and State Key Laboratory of Networking and Switching Technology Beijing100876 China

The Internet of Things technology, through the deployment of sensors and intelligent traffic cameras, facilitates the collection, processing, and analysis of traffic flow, vehicle density, and road conditions. However, traffic image data contains a substantial amount of personal sensitive information. Therefore, implementing hierarchical encryption on images is crucial for preventing the leakage of personal privacy and ensuring data is used in compliance with regulations. Moreover, the rise of quantum computing poses a substantial threat to existing key distribution systems, especially for resource-constrained IoT devices. To address these challenges, this paper presents a lightweight hierarchical privacy protection scheme for traffic images that addresses key adaptability, quantum threats, and hierarchical privacy protection. The scheme includes a lattice-based public-key algorithm with updatable public and private keys to ensure quantum-resistant and forward security. It also introduces, for the first time, a hierarchical tree-structured encryption scheme based on the SHA3 hash function and the homomorphic property of compressed sensing, allowing high-permission users to generate keys for low-permission users without compromising the quality of image decryption. Additionally, the scheme includes a compressed sensing public-key encryption algorithm based on chaotic systems and the difficulty of matrix factorization, which supports sampling of images of any size, enhancing adaptability and reducing resource consumption. Tests indicate that this image encryption algorithm can resist various statistical analyses, achieving a high NPCR of 99.6277%. In summary, our research significantly contributes to the effective safeguarding of personal data security in resource-constrained IoT environments, particularly in the face of potential quantum computing threats. © 2025 IEEE.

关键词： Matrix factorization

来源：评论

学校读者我要写书评

暂无评论

Evolutionary Game-Based Vertical Handover Strategy for Space-Air-Ground Integrated Network

Evolutionary Game-Based Vertical Handover Strategy for Space...

引用

IEEE Wireless Communications and networking Conference (WCNC)

作者： Zhou, Yiting Meng, Rui Xiong, Huachao Han, Shujun Xu, Xiaodong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

ISBN: (纸本)9781665491228

Space-Air-Ground Integrated Network (SAGIN) has recently attracted extensive attention as a new type of network architecture, which can meet the ever-increasing demands of users for ubiquitous access. However, due to different coverage performance of various networks and the demands of huge capacity in ultra-dense regions, frequent passive group handover will occur, thereby decreasing the quality of service (QoS) and causing signaling storms. To tackle this problem, we introduce low Earth orbit (LEO) satellites, high-altitude platforms and ground base stations to cover ultra-dense regions. The mobility management functions are configured in LEO satellites, which serve as a central controller and compute the average utility based on QoS. We propose an evolutionary game-based vertical handover scheme, where the users covered by SAGINs are modeled as players to compete limited network resources. Simulation results verified the effectiveness of the proposed scheme in meeting the QoS while improving the utility of networks.

关键词： SAGIN vertical handover evolutionary game

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：