检索结果-内蒙古大学图书馆

Joint Task Offloading and Resource Allocation for Space-Air-Ground Collaborative Network

DRONES 2023年第7期7卷

作者： Mei, Chengli Gao, Cheng Wang, Heng Xing, Yanxia Ju, Ningyao Hu, Bo Chinatelecom Res Inst Beijing 102209 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

The space-air-ground collaborative network can provide computing service for ground users in remote areas by deploying edge servers on satellites and high-altitude platform (HAP) drones. However, with the growing number of ground devices required to be severed, it becomes imperative to address the issue of spectrum demand for the HAP drone to meet the access of a large number of users. In addition, the long propagation distance between devices and the HAP drone, and between the HAP drone and LEO satellites, will lead to high data transmission energy consumption. Motivated by these factors, we introduce a space-air-ground collaborative network that employs the non-orthogonal multiple access (NOMA) technique, enabling all ground devices to access the HAP drone. Therefore, all devices can share the same communication spectrum. Furthermore, the HAP drone can process part of the ground devices' tasks locally, and offload the rest to satellites within the visible range for processing. Based on this system, we formulate a weighted energy consumption minimization problem considering power control, computing frequency allocation, and task-offloading decision. The problem is solved by the proposed low-complexity iterative algorithm. Specifically, the original problem is decomposed into interconnected coupled subproblems using the block coordinate descent (BCD) method. The first subproblem is to optimize power control and computing frequency allocation, which is solved by a convex algorithm after a series of transformations. The second subproblem is to make an optimal task-offloading strategy, and we solve it using the concave-convex procedure (CCP)-based algorithm after penalty-based transformation on binary variables. Simulation results verify the convergence and performance of the proposed iterative algorithm compared with the two benchmark algorithms.

关键词： space-ground-air collaborative network mobile edge computing drone communication non-orthogonal multiple access (NOMA) task offloading and resource allocation

来源：评论

学校读者我要写书评

暂无评论

Modeling and Performance Analysis of Multiserver Cloud Database Over Quasi-Static Rayleigh Fading Channel

引用

IEEE INTERNET OF THINGS JOURNAL 2024年第11期11卷 20314-20326页

作者： Chen, Mengying Liu, Yang Dong, Chen An, Wannian Xu, Xiaodong Zhang, Ping Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

With the development of communication in the post-5G era, the combination of communication and cloud computing becomes closer. In order to promote the further development of cloud-network, this article will study the performance of Multiserver cloud Database under the Communication quality of quasi-static Rayleigh fading channel with multiple antennas (MC-MD). The CLIENTS with unlimited customers, a COMMUNICATION SYSTEM subject to quasi-static Rayleigh fading, and CLOUD DATABASE with two-phase locking protocol are the three components of the MC-MD model. Transactions are 1)initiated by the CLIENTS, 2)transmitted to the CLOUD DATABASE through the COMMUNICATION SYSTEM for processing, 3)then returned to the CLIENTS. The indicators of the model is mathematically derived by using queuing theory. These include client's indicators [average concurrent quantity of the system in steady state (CQ), average transactions stay time of the system in steady state (ST), average queue length of the waiting area in steady state (QL), and average transactions wait time of the waiting area in steady state (WT)] and server's indicator [average number of service desks in the busy period at steady state (DN)]. Under the appropriate conditions, the results indicate that the theoretical value of service performance is basically consistent with the simulation value. Clearly, the high speed improves the service performance of the system and decreases the service pressure. On the basis of this, the optimization strategy is proposed and the simulation indicators Jitter of transactions sojourn time of the system in steady state (STJ) is added. The results show that the transaction scheduling optimization strategy effectively reduce the delay and its jitter.

关键词： Databases Cloud computing Protocols Distributed databases Analytical models Computational modeling Servers Exclusive lock multiserver cloud database quasi-static Rayleigh fading channel with multiple antennas queue system shared lock

来源：评论

学校读者我要写书评

暂无评论

Dynamic and Static Representation Learning Network for Recommendation

引用

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024年第1期35卷 831-841页

作者： Liu, Tongcun Lou, Siyuan Liao, Jianxin Feng, Hailin Zhejiang A&F Univ Sch Math & Comp Sci Hangzhou 311300 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Existing review-based recommendation methods learn a latent representation of user and item from user-generated reviews by a static strategy, which are unable to capture the dynamic evolution of users' interests and the dynamic attraction of items. Here, we propose a dynamic and static representation learning network (DSRLN) to improve the rating prediction accuracy by exploring fine-grained representations of users and items. Specifically, we built DSRLN with a dynamic representation extractor to model the dynamic evolution of users' interests by exploring the inner relations of an interaction sequence, and with a static representation extractor to model the users' intrinsic preferences by learning the semantic coherence and feature strength information from reviews. To identify the different influences of dynamic and static features for different users, a personalized adaptive fusion module was designed using a weighted attention mechanism. Extensive experiments on five real-world datasets from Amazon demonstrated the superiority of the proposed model, and the additional ablation studies verified the effectiveness of the components designed in the DSRLN model.

关键词： Adaptation models Semantics Representation learning Recommender systems Feature extraction Data models Data mining Adaptive fusion strategy attention mechanism recommender system representation learning

来源：评论

学校读者我要写书评

暂无评论

Energy- and Quality-Aware Task Offloading for WebVR Service in Terminal-Aided Mobile Edge Network

引用

IEEE TRANSACTIONS ON VEHICULAR technology 2022年第8期71卷 8825-8838页

作者： Yang, Yang Feng, Lei Que, Xiaoyu Zhou, Fanqin Li, Wenjing Beijing Univ Posts & Telecommun BUPT State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Web virtual reality (WebVR) is gaining increasing attention as interactive VR experiences become more prevalent. The high energy consumption and strict quality requirements are still significant challenges for its application in the mobile edge network. In this context, content caching and task offloading are promising solutions to save the energy of WebVR. This paper proposes a hybrid decentralized offloading architecture in which the MEC server and multiple terminals jointly participate in the caching and processing of WebVR tasks. In this framework, the graph convolutional network and unsupervised clustering algorithm are jointly applied to process the WebVR service feature graph to achieve FoV-level content caching. Moreover, WebVR users with idle computing resources assist neighboring users with performing tasks. On this basis, we propose a distributed low-bound-based alternative direction method of multiplier (LADMM) algorithm to optimize the offloading mode and the allocation of tasks and computing power resources to minimize system energy consumption. The proposed offloading mode can lower energy consumption while maintaining a good balance between delay performance and resource utilization.

关键词： Task analysis Servers Device-to-device communication Energy consumption Delays Videos Rendering (computer graphics) Device-to-device energy-saving quality awareness task caching and offloading WebVR service WebVR feature map

来源：评论

学校读者我要写书评

暂无评论

RACC: Rapid and Accurate INT-Based Congestion Control in RDMA Network

RACC: Rapid and Accurate INT-Based Congestion Control in RDM...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhao, Yanzhe Wang, Shuo Han, Siyu Zhou, Dong Peng, Guoyu Huang, Tao Bupt State Key Laboratory of Networking and Switching Technology Beijing100876 China Purple Mountain Laboratories Nanjing211111 China

ISBN: (纸本)9798350351255

With the rapid growth of network speed, datacenter applications have increasing demands on networks for high throughput and ultra-low latency. RDMA is widely deployed due to its high performance. Most existing RDMA congestion control schemes employ end-to-end architecture with inherent feedback delays of at least one Round-Trip Time (RTT).To overcome these limitations, we propose RACC, a rapid and accurate INT-Based RDMA congestion control scheme. The switches directly provide INT feedback, reducing the feedback signal latency. In addition, the adaptive rate update mechanism is adopted at the sender, which enhances the rapid response to network congestion and the stable control of in-flight bytes. We conduct simulation experiments based on the Fat-Tree topology to analyze the requirements for datacenter performance metrics including convergence, fairness, and dynamic queues. Our evaluations show that the peak queue lengths are reduced by up to 80% compared to HPCC and PowerTCP, and the convergence time after congestion is reduced by half. © 2024 IEEE.

关键词： Congestion control (communication)

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Network Access Security Assessment System Based on Trustworthy Federated Learning 14th

Design and Implementation of Network Access Security Assessm...

引用

14th International Conference on Computer Engineering and Networks, CENet 2024

作者： Wu, Shuhao Zhen, Zerui Wu, Haifeng Feng, Lei Zhou, Fanqin Gao, Peng Bai, Haoyang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China State Grid Beijing Electric Power Company Beijing China

ISBN: (纸本)9789819642441

With the development of attack methods in the information age, the traditional rule-based network access and security assessment can hardly meet the demand. This paper focuses on the design and implementation of a network access security assessment system, which uses trustworthy federated learning technology to solve the problem of multi-participant collaborative training of security state detection models. The system uses the trustworthy federated learning module to determine the piecewise aggregation scheme before model aggregation and identifies and removes malicious participants during the aggregation process. The robustness and adaptability of the system are improved through layered and modularized design. Experimental results show that the designed system is capable of continuous access authentication and security state assessment of network devices in energy Internet scenarios, and collaboratively trains network state assessment models using the trustworthy federated training process. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

RHCC: Revisiting Intra-Host Congestion Control in RDMA Networks

IEEE TRANSACTIONS ON NETWORKING

引用

IEEE TRANSACTIONS ON networking 2025年第3期33卷 1189-1202页

作者： Wan, Zirui Zhang, Jiao Wang, Yuxiang Liu, Kefei Pan, Haoyu Pan, Yongchen Huang, Tao Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China

RDMA has been widely deployed in production datacenters. The conventional wisdom believes that the intra-host network delivers stable and high performance. However, intra-host resources witness a relative stagnation in technology trends compared to the evolving RDMA NIC (RNIC). Thus, the RNIC traffic may not get sufficient intra-host resources when it contends with CPU-to-memory traffic. A line of recent works from large-scale production datacenter operators demonstrates the emergence of intra-host congestion and associated performance collapse, which forces us to revisit the practice of intra-host congestion control. However, the ability to efficiently control RDMA intra-host networks is far less mature than inter-host networks, which brings challenges in congestion monitoring, intra-host resource allocation and RNIC traffic adjustment. In this paper, we propose RDMA intra-Host Congestion Control (RHCC), which combines CPU-to-memory traffic congestion avoidance with sub-RTT granularity and proactive RNIC traffic adjustment. RHCC ensures fast congestion avoidance and can work with different inter-host congestion control methods. We implement RHCC on commodity servers and RNICs and conduct experiments to evaluate the performance. The results show that RHCC can increase/decrease the network throughput/latency by up to 2x and 1.4x, respectively.

关键词： RDMA network intra-host network congestion control RDMA network intra-host network congestion control

来源：评论

学校读者我要写书评

暂无评论

TRCT: A Traceable Anonymous Transaction Protocol for Blockchain

引用

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2023年 18卷 4391-4405页

作者： Duan, Junke Wang, Licheng Wang, Wei Gu, Lize Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Inst Technol Beijing 100081 Peoples R China

Anonymous cryptocurrencies are distributed applications based on blockchain technology that enhance the anonymity of user transactions. However, they also provide cover for many criminal activities. Existing traceable modifications of anonymous transaction protocols do not support public verification of the traceability of transactions, meaning dishonest users can still evade tracing by forging partial proofs. In this paper, we first propose EPoK, which is a partially extractable zero-knowledge proof scheme designed to address this issue. We provide the instantiation of EPoK, as well as its formal security proofs. Combined with EPoK and the classic anonymous transaction protocol RingCT, we propose a traceable anonymous transaction protocol TRCT for tracing participants' addresses and transaction amounts in anonymous transactions. Compared to previous works, TRCT is the first to implement public verification of the transaction's traceability while still maintaining anonymity. This ensures that users cannot forge relevant proofs to evade tracing. We present and prove the security properties of TRCT, and experimentally compare its efficiency with the original RingCT protocol. The result shows that the extra overhead generated by TRCT is small.

关键词： Blockchain cryptocurrency anonymity RingCT traceability

来源：评论

学校读者我要写书评

暂无评论

REWAFL: Residual Energy and Wireless Aware Participant Selection for Efficient Federated Learning Over Mobile Devices

引用

IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第10期23卷 9487-9501页

作者： Li, Yixuan Qin, Xiaoqi Geng, Jiaxiang Chen, Rui Hou, Yanzhao Gong, Yanmin Pan, Miao Zhang, Ping Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Peng Cheng Lab Dept Broadband Commun Shenzhen 518066 Peoples R China

Participant selection (PS) helps to accelerate federated learning (FL) convergence, which is essential for the practical deployment of FL over mobile devices. While most existing PS approaches focus on improving training accuracy and efficiency rather than residual energy of mobile devices, which fundamentally determines whether the selected devices can participate. Meanwhile, the impacts of mobile devices heterogeneous wireless transmission rates on PS and FL training efficiency are largely ignored. Moreover, PS causes the staleness issue. Prior research exploits isolated functions to force long-neglected devices to participate, which is decoupled from original PS designs. In this paper, we propose a residual energy and wireless aware PS design for efficient FL training over mobile devices (REWAFL). REWAFL introduces a novel PS utility function that jointly considers global FL training utilities and local energy utility, which integrates energy consumption and residual battery energy of candidate mobile devices. Under the proposed PS utility function framework, REWAFL further presents a residual energy and wireless aware local computing policy. Besides, REWAFL buries the staleness solution into its utility function and local computing policy. The experimental results show that REWAFL is effective in improving training accuracy and efficiency, while avoiding flat battery of mobile devices.

关键词： Training Mobile handsets Wireless communication Computational modeling Servers Energy consumption Batteries Federated learning mobile devices participant selection residual energy awareness

来源：评论

学校读者我要写书评

暂无评论

Learning-Based Task-Centric Multi-User Semantic Communication Solution for Vehicle Networks

引用

IEEE Transactions on Vehicular technology 2025年第6期74卷 9328-9342页

作者： Yuan, Yifan Zhang, Jingxuan Xu, Xiaodong Wang, Bizhu Han, Shujun Sun, Mengying Zhang, Ping University of Science and Technology Beijing National School of Elite Engineering Beijing100083 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Peng Cheng Laboratory Shenzhen518066 China

With the application of 5 G in in-vehicle network scenarios, the inevitable crisis of scarcity of communication resources is deepening. At the same time, considering the high demands for communication delay in vehicular network scenarios, it is essential to meet the requirements for reliable information transmission in high-speed mobility environments. To address these issues, we propose the Task-Centric Multi-User Semantic Communication (TCMSC) solution, designed to meet the energy consumption and transmission time delay requirements in line with the new paradigm of semantic communication. Our solution introduces a task-centric semantic processing model aimed at improving Semantic Spectral Efficiency (S-SE). The TCMSC solution is tailored for multi-service vehicle scenarios, optimizing power consumption and enhancing reliability, making it well-suited for challenging environments. Moreover, we propose a novel method using Stochastic Network Calculus (SNC) to accurately model semantic task delay and calculate the upper bound of Vehicle-to-Infrastructure (V2I) delay-bound violation probability. However, to tackle the increased optimization complexity from SNC while simultaneously enhancing feature extraction, we propose the Transformer Advantage Actor Critic (TR-A2C) algorithm. This algorithm leverages the Transformer to capture dynamic vehicle parameters across scenarios, accelerating the TCMSC solution. Experimental results demonstrate that, compared to traditional single-service vehicle dispatch, TCMSC improves delay violation probability by 2.88 and reduces power consumption by 31.1all while effectively enhancing S-SE in complex traffic environments. © 1967-2012 IEEE.

关键词： Stochastic systems

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：