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Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

China Communications 2024年第4期21卷 38-52页

作者： Jiang Fan Qin Junwei Liu Lei Tian Hui School of Communications and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China State Key Laboratory of networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy co

关键词： associative tasks cache-aided procedure double deep Q-network Internet of Medical Things(IoMT) multi-access edge computing(MEC)

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Resource Allocation for Cognitive network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning

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China Communications 2024年第6期21卷 53-68页

作者： Zhang Zhenyu Zhang Yong Yuan Siyu Cheng Zhenjie School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Work Safety Intelligent Monitoring(Beijing University of Posts and telecommunications) Beijing 100876China

In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay *** users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)*** design the Double Deep Q network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation *** objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of *** results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS ***,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.

关键词： cognitive radio deep reinforcement learning network slicing power-domain non-orthogonal multiple access resource allocation

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Finite-time tracking control of heterogeneous multi-AUV systems with partial measurements and intermittent communication

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Science China(Information Sciences) 2024年第5期67卷 165-182页

作者： Bo CHEN Jiangping HU Bijoy Kumar GHOSH School of Automation Engineering University of Electronic Science and Technology of China Key Laboratory of Intelligent Analysis and Decision on Complex systems Chongqing University of Posts and Telecommunications Yangtze Delta Region Institute (Huzhou) University of Electronic Science and Technology of China Department of Mathematics and Statistics Texas Tech University

The development of a distributed trajectory-tracking control strategy that is independent of velocity measurements is critical to achieving finite-time tracking control of autonomous underwater vehicle(AUV) systems. In this study, a group of heterogeneous AUV systems with intermittent communication links is considered and a finite-time trajectory-tracking control strategy is developed. The strategy includes two observers and one controller proposed for each follower-AUV. The first observer, a hybrid finite-time observer,estimates the state of the leader, whereas the second observer, which relies only on the position measurement,is proposed to estimate the states of the follower-AUV itself. In addition, a distributed trajectory-tracking controller is designed using the states estimated by the intermittent communication network even without velocity measurements. A homogeneous technique is utilized to prove that all followers can track the leader in a finite time. Finally, the effectiveness of the developed finite-time tracking control strategy is illustrated by numerical simulations.

关键词： distributed observer finite-time tracking homogeneous technique intermittent communication multiple heterogeneous AUVs

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Convolutional neural network adaptation and optimization method in SIMT computing mode

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The Journal of China Universities of Posts and telecommunications 2024年第2期31卷 105-112页

作者： Feng Zhenfu Zhang Yaying Yang Lele Xing Lidong School of Electronic Engineering Xi'an University of Posts and TelecommunicationsXi'an 710121China

For studying and optimizing the performance of general-purpose computing on graphics processing units(GPGPU)based on single instruction multiple threads(SIMT)processor about the neural network application,this work contributes a self-developed SIMT processor named Pomelo and correlated assembly *** parallel mechanism of SIMT computing mode and self-developed Pomelo processor is briefly introduced.A common convolutional neural network(CNN)is built to verify the compatibility and functionality of the Pomelo *** computing flow with task level and hardware level optimization is adopted on the Pomelo processor.A specific algorithm for organizing a Z-shaped memory structure is developed,which addresses reducing memory access in mass data computing *** the above-combined adaptation and optimization strategy,the experimental result demonstrates that reducing memory access in SIMT computing mode plays a crucial role in improving performance.A 6.52 times performance is achieved on the 4 processing elements case.

关键词： parallel computing single instruction multiple threads(SIMT) convolutional neural network(CNN) memory optimization

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Actor-Critic-Based UAV-Assisted Data Collection in the Wireless Sensor network

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China Communications 2024年第4期21卷 163-177页

作者： Huang Xiaoge Wang Lingzhi He Yong Chen Qianbin School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China

Wireless Sensor network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible ***,WSN data collection encounters challenges in scenarios lacking communication *** aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high *** this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the ***,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial *** ground layer senses the environmental data by the cluster members(CMs),and the CMs transmit the data to the cluster heads(CHs),which forward the collected data to the *** aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for ***,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of ***,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with ***,simulation results verify the effectiveness of the proposed algorithms.

关键词： actor critic data collection deep reinforcement learning unmanned aerial vehicle wireless sensor network

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A Novel Multi-Stream Fusion network for Underwater Image Enhancement

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China Communications 2024年第2期21卷 166-182页

作者： Guijin Tang Lian Duan Haitao Zhao Feng Liu Jiangsu Key Laboratory of Image Processing and Image Communication Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing 210003China

Due to the selective absorption of light and the existence of a large number of floating media in sea water, underwater images often suffer from color casts and detail blurs. It is therefore necessary to perform color correction and detail restoration. However,the existing enhancement algorithms cannot achieve the desired results. In order to solve the above problems, this paper proposes a multi-stream feature fusion network. First, an underwater image is preprocessed to obtain potential information from the illumination stream, color stream and structure stream by histogram equalization with contrast limitation, gamma correction and white balance, respectively. Next, these three streams and the original raw stream are sent to the residual blocks to extract the features. The features will be subsequently fused. It can enhance feature representation in underwater images. In the meantime, a composite loss function including three terms is used to ensure the quality of the enhanced image from the three aspects of color balance, structure preservation and image smoothness. Therefore, the enhanced image is more in line with human visual ***, the effectiveness of the proposed method is verified by comparison experiments with many stateof-the-art underwater image enhancement algorithms. Experimental results show that the proposed method provides superior results over them in terms of MSE,PSNR, SSIM, UIQM and UCIQE, and the enhanced images are more similar to their ground truth images.

关键词： image enhancement multi-stream fusion underwater image

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GNN-based temporal knowledge reasoning for UAV mission planning systems

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The Journal of China Universities of Posts and telecommunications 2024年第1期31卷 12-25页

作者： Chai Rong Duan Xiaofang Wang Lixuan School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China

Unmanned aerial vehicles(UAVs)are increasingly applied in various mission scenarios for their versatility,scalability and *** UAV mission planning systems(UMPSs),an efficient mission planning strategy is essential to meet the requirements of UAV ***,rapidly changing environments and unforeseen threats pose challenges to UMPSs,making efficient mission planning *** address these challenges,knowledge graph technology can be utilized to manage the complex relations and constraints among UAVs,missions,and *** paper investigates knowledge graph application in UMPSs,exploring its modeling,representation,and storage concepts and ***,the construction of a specialized knowledge graph for UMPS is ***,the paper delves into knowledge reasoning within UMPSs,emphasizing its significance in timely updates in the dynamic environment.A graph neural network(GNN)-based approach is proposed for knowledge reasoning,leveraging GNNs to capture structural information and accurately predict missing entities or relations in the knowledge *** relation reasoning,path information is also incorporated to improve the accuracy of *** account for the temporal dynamics of the environment in UMPS,the influence of timestamps is captured through the attention *** effectiveness and applicability of the proposed knowledge reasoning method are verified via simulations.

关键词： unmanned aerial vehicle mission planning knowledge graph knowledge reasoning graph neural network

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A Blind Batch Encryption and Public Ledger-Based Protocol for Sharing Sensitive Data

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China Communications 2024年第1期21卷 310-322页

作者： Zhiwei Wang Nianhua Yang Qingqing Chen Wei Shen Zhiying Zhang School of Computer Sciences Nanjing University of Posts and TelecommunicationsNanjing 210023China dept.of Intelligent Science and Information Law East China University of Political Science and LawShanghai 201620China Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal UniversityHaikou 571158China State Key Laboratory of Public Big Data Guizhou UniversityGuizhou 550025China Yunnan Key Laboratory of Blockchain Application Technology Yunnan Innovation Research Institute of Beijing University of Aeronautics and AstronauticsKunming 650233

For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be *** owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the *** prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file *** also provide security analysis in the context of four typical attacks.

关键词： blind batch encryption data sharing onetime adaptive access public ledger security and privacy

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Design of High Performance MXene/Oxide Structure Memristors for Image Recognition Applications

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Chinese Journal of Electronics 2024年第2期33卷 336-345页

作者： Xiaojuan LIAN Yuelin SHI Xinyi SHEN Xiang WAN Zhikuang CAI Lei WANG The College of Integrated Circuit Science and Engineering Nanjing University of Posts and Telecommunications The National and Local Joint Engineering Laboratory of RF Integration and Micro-Assembly Technology Nanjing University of Posts and Telecommunications

Recent popularity to realize image recognition by memristor-based neural network hardware systems has been witnessed owing to their similarities to neurons and ***,the stochastic formation of conductive filaments inside the oxide memristor devices inevitably makes them face some drawbacks,represented by relatively higher power consumption and severer resistance switching *** this work,we design and fabricate the Ag/MXene（Ti3C2）/SiO2/Pt memristor after considering the stronger interactions between Ti3C2and Ag ions,which lead to a Ti3C2/SiO2structure memristor owning to much lower "SET" voltage and smaller resistance switching fluctuation than pure ***,the conductances of the Ag/Ti3C2/SiO2/Pt memristor have been modulated by changing the number of the applied programming pulse,and two typical biological behaviors,i.e.,longterm potentiation and long-term depression,have been ***,device conductances are introduced into an integrated device-to-algorithm framework as synaptic weights,by which the MNIST hand-written digits are recognized with accuracy up to 77.39%.

关键词： Performance evaluation Silicon compounds Image recognition Power demand Memristors Switches Programming

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Joint Allocation of Computing and Connectivity Resources in Survivable Inter-Datacenter Elastic Optical networks

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China Communications 2024年第8期21卷 172-181页

作者： Yang Tao Li Yang Chen Xue State Key Lab of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China Cloud network Department China Telecom Group Beijing CorporationBeijing 100010China

Inter-datacenter elastic optical networks(EON)need to provide the service for the requests of cloud computing that require not only connectivity and computing resources but also network *** this paper,to realize joint allocation of computing and connectivity resources in survivable inter-datacenter EONs,a survivable routing,modulation level,spectrum,and computing resource allocation algorithm(SRMLSCRA)algorithm and three datacenter selection strategies,*** Resource First(CRF),Shortest Path First(SPF)and Random Destination(RD),are proposed for different *** and manycast are applied to the communication of computing requests,and the routing strategies are calculated *** results show that SRMLCRA-CRF can serve the largest amount of protected computing tasks,and the requested calculation blocking probability is reduced by 29.2%,28.3%and 30.5%compared with SRMLSCRA-SPF,SRMLSCRA-RD and the benchmark EPS-RMSA algorithms ***,it is more applicable to the networks with huge ***,SRMLSCRA-SPF consumes the least spectrum,thereby exhibiting its suitability for scenarios where the amount of calculation is small and communication resources are *** results demonstrate that the proposed methods realize the joint allocation of computing and connectivity resources,and could provide efficient protection for services under single-link failure and occupy less spectrum.

关键词： computing and connectivity interdatacenter networks joint resource allocation service protection

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