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数字通信与网络（英文）
数字通信与网络（英文）

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数字通信与网络（英文）/CSCD北大核心SCI
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    Fast UAV path planning in urban environments based on three-step experience buffer sampling DDPG

    Shasha TianYuanxiang LiXiao ZhangLu Zheng...
    813-826页
    查看更多>>摘要：The path planning of Unmanned Aerial Vehicle(UAV)is a critical issue in emergency communication and rescue operations,especially in adversarial urban environments.Due to the continuity of the flying space,complex building obstacles,and the aircraft's high dynamics,traditional algorithms cannot find the optimal collision-free flying path between the UAV station and the destination.Accordingly,in this paper,we study the fast UAV path planning problem in a 3D urban environment from a source point to a target point and propose a Three-Step Experience Buffer Deep Deterministic Policy Gradient(TSEB-DDPG)algorithm.We first build the 3D model of a complex urban environment with buildings and project the 3D building surface into many 2D geometric shapes.After transformation,we propose the Hierarchical Learning Particle Swarm Optimization(HL-PSO)to obtain the empirical path.Then,to ensure the accuracy of the obtained paths,the empirical path,the collision information and fast transition information are stored in the three experience buffers of the TSEB-DDPG algorithm as dynamic guidance information.The sampling ratio of each buffer is dynamically adapted to the training stages.Moreover,we designed a reward mechanism to improve the convergence speed of the DDPG algorithm for UAV path planning.The proposed TSEB-DDPG algorithm has also been compared to three widely used competitors experimentally,and the results show that the TSEB-DDPG algorithm can archive the fastest convergence speed and the highest accuracy.We also conduct experiments in real scenarios and compare the real path planning obtained by the HL-PSO algorithm,DDPG algorithm,and TSEB-DDPG algorithm.The results show that the TSEB-DDPG algorithm can archive almost the best in terms of accuracy,the average time of actual path planning,and the success rate.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    Energy-optimal DNN model placement in UAV-enabled edge computing networks

    Jianhang TangGuoquan WuMohammad Mussadiq JalalzaiLin Wang...
    827-836页
    查看更多>>摘要：Unmanned aerial vehicle(UAV)-enabled edge computing is emerging as a potential enabler for Artificial Intel-ligence of Things(AIoT)in the forthcoming sixth-generation(6G)communication networks.With the use of flexible UAVs,massive sensing data is gathered and processed promptly without considering geographical lo-cations.Deep neural networks(DNNs)are becoming a driving force to extract valuable information from sensing data.However,the lightweight servers installed on UAVs are not able to meet the extremely high requirements of inference tasks due to the limited battery capacities of UAVs.In this work,we investigate a DNN model placement problem for AIoT applications,where the trained DNN models are selected and placed on UAVs to execute inference tasks locally.It is impractical to obtain future DNN model request profiles and system operation states in UAV-enabled edge computing.The Lyapunov optimization technique is leveraged for the proposed DNN model placement problem.Based on the observed system overview,an advanced online placement(AOP)algorithm is developed to solve the transformed problem in each time slot,which can reduce DNN model transmission delay and disk I/O energy cost simultaneously while keeping the input data queues stable.Finally,extensive simulations are provided to depict the effectiveness of the AOP algorithm.The numerical results demonstrate that the AOP algorithm can reduce 18.14％of the model placement cost and 29.89％of the input data queue backlog on average by comparing it with benchmark algorithms.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    UAV-supported intelligent truth discovery to achieve low-cost communications in mobile crowd sensing

    Jing BaiJinsong GuiGuosheng HuangShaobo Zhang...
    837-852页
    查看更多>>摘要：Unmanned and aerial systems as interactors among different system components for communications,have opened up great opportunities for truth data discovery in Mobile Crowd Sensing(MCS)which has not been properly solved in the literature.In this paper,an Unmanned Aerial Vehicles-supported Intelligent Truth Dis-covery(UAV-ITD)scheme is proposed to obtain truth data at low-cost communications for MCS.The main in-novations of the UAV-ITD scheme are as follows:(1)UAV-ITD scheme takes the first step in employing UAV joint Deep Matrix Factorization(DMF)to discover truth data based on the trust mechanism for an Information Elici-tation Without Verification(IEWV)problem in MCS.(2)This paper introduces a truth data discovery scheme for the first time that only needs to collect a part of n data samples to infer the data of the entire network with high accuracy,which saves more communication costs than most previous data collection schemes,where they collect n or kn data samples.Finally,we conducted extensive experiments to evaluate the UAV-ITD scheme.The results show that compared with previous schemes,our scheme can reduce estimated truth error by 52.25％-96.09％,increase the accuracy of workers'trust evaluation by 0.68-61.82 times,and save recruitment costs by 24.08％-54.15％in truth data discovery.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    DTAIS:Distributed trusted active identity resolution systems for the Industrial Internet

    Tao HuangRenchao XieYuzheng RenF.Richard Yu...
    853-862页
    查看更多>>摘要：In recent years,the Industrial Internet and Industry 4.0 came into being.With the development of modern industrial intelligent manufacturing technology,digital twins,Web3 and many other digital entity applications are also proposed.These applications apply architectures such as distributed learning,resource sharing,and arithmetic trading,which make high demands on identity authentication,asset authentication,resource addressing,and service location.Therefore,an efficient,secure,and trustworthy Industrial Internet identity resolution system is needed.However,most of the traditional identity resolution systems follow DNS architecture or tree structure,which has the risk of a single point of failure and DDoS attack.And they cannot guarantee the security and privacy of digital identity,personal assets,and device information.So we consider a decentralized approach for identity management,identity authentication,and asset verification.In this paper,we propose a distributed trusted active identity resolution system based on the inter-planetary file system(IPFS)and non-fungible token(NFT),which can provide distributed identity resolution services.And we have designed the system architecture,identity service process,load balancing strategy and smart contract service.In addition,we use Jmeter to verify the performance of the system,and the results show that the system has good high concurrent performance and robustness.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    Strengthening network slicing for Industrial Internet with deep reinforcement learning

    Yawen TanJiadai WangJiajia Liu
    863-872页
    查看更多>>摘要：Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value chain.Its highly heterogeneous network structure and diversified application requirements call for the applying of network slicing technology.Guaranteeing robust network slicing is essential for Industrial Internet,but it faces the challenge of complex slice topologies caused by the intricate interaction relationships among Network Functions(NFs)composing the slice.Existing works have not concerned the strengthening problem of industrial network slicing regarding its complex network properties.Towards this end,we aim to study this issue by intelligently selecting a subset of most valuable NFs with the minimum cost to satisfy the strengthening requirements.State-of-the-art AlphaGo series of algorithms and the advanced graph neural network technology are combined to build the solution.Simulation results demonstrate the superior performance of our scheme compared to the benchmark schemes.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    Unmanned aerial vehicles towards future Industrial Internet:Roles and opportunities

    Linpei LiChunlei SunJiahao HuoYu Su...
    873-883页
    查看更多>>摘要：Unmanned Aerial Vehicles(UAVs)are gaining increasing attention in many fields,such as military,logistics,and hazardous site mapping.Utilizing UAVs to assist communications is one of the promising applications and research directions.The future Industrial Internet places higher demands on communication quality.The easy deployment,dynamic mobility,and low cost of UAVs make them a viable tool for wireless communication in the Industrial Internet.Therefore,UAVs are considered as an integral part of Industry 4.0.In this article,three typical use cases of UAVs-assisted communications in Industrial Internet are first summarized.Then,the state-of-the-art technologies for drone-assisted communication in support of the Industrial Internet are presented.According to the current research,it can be assumed that UAV-assisted communication can support the future Industrial Internet to a certain extent.Finally,the potential research directions and open challenges in UAV-assisted communications in the upcoming future Industrial Internet are discussed.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    A compatible carbon efficiency information service framework based on the industrial internet identification

    Cheng ChiYang LiuBaoluo MaSenchun Chai...
    884-894页
    查看更多>>摘要：Green and low-carbon is a new development model that seeks balance between environmental sustainability and high economic growth.If explainable and available carbon emission data can be accurately obtained,it will help policy regulators and enterprise managers to more accurately implement this development strategy.A lot of research has been carried out,but it is still a difficult problem that how to accommodate and adapt the complex carbon emission data computing models and factor libraries developed by different regions,different industries and different enterprises.Meanwhile,with the rapid development of the Industrial Internet,it has not only been used for the supply chain optimization and intelligent scheduling of the manufacturing industry,but also been used by more and more industries as an important way of digital transformation.Especially in China,the In-dustrial Internet identification and resolution system is becoming an important digital infrastructure to uniquely identify objects and share data.Hence,a compatible carbon efficiency information service framework based on the Industrial Internet Identification is proposed in this paper to address the problem of computing and querying multi-source heterogeneous carbon emission data.We have defined a multi cooperation carbon emission data interaction model consisting of three roles and three basic operations.Further,the implementation of the framework includes carbon emission data identification,modeling,calculation,query and sharing.The practice results show that its capability and effectiveness in improving the responsiveness,accuracy,and credibility of compatible carbon efficiency data query and sharing services.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    Towards privacy-preserving and efficient word vector learning for lightweight IoT devices

    Nan JiaShaojing FuGuangquan XuKai Huang...
    895-903页
    查看更多>>摘要：Nowadays,Internet of Things(IoT)is widely deployed and brings great opportunities to change people's daily life.To realize more effective human-computer interaction in the IoT applications,the Question Answering(QA)systems implanted in the IoT services are supposed to improve the ability to understand natural language.Therefore,the distributed representation of words,which contains more semantic or syntactic information,has been playing a more and more important role in the QA systems.However,learning high-quality distributed word vectors requires lots of storage and computing resources,hence it cannot be deployed on the resource-constrained IoT devices.It is a good choice to outsource the data and computation to the cloud servers.Nevertheless,it could cause privacy risks to directly upload private data to the untrusted cloud.Therefore,realizing the word vector learning process over untrusted cloud servers without privacy leakage is an urgent and challenging task.In this paper,we present a novel efficient word vector learning scheme over encrypted data.We first design a series of arithmetic computation protocols.Then we use two non-colluding cloud servers to implement high-quality word vectors learning over encrypted data.The proposed scheme allows us to perform training word vectors on the remote cloud servers while protecting privacy.Security analysis and experiments over real data sets demonstrate that our scheme is more secure and efficient than existing privacy-preserving word vector learning schemes.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    Hybrid millimeter wave heterogeneous networks with spatially correlated user equipment

    Arif UllahZiaul Haq AbbasGhulam AbbasFazal Muhammad...
    904-917页
    查看更多>>摘要：In this paper,we analyze a hybrid Heterogeneous Cellular Network(HCNet)framework by deploying millimeter Wave(mmWave)small cells with coexisting traditional sub-6GHz macro cells to achieve improved coverage and high data rate.We consider randomly-deployed macro base stations throughout the network whereas mmWave Small Base Stations(SBSs)are deployed in the areas with high User Equipment(UE)density.Such user centric deployment of mmWave SBSs inevitably incurs correlation between UE and SBSs.For a realistic scenario where the UEs are distributed according to Poisson cluster process and directional beamforming with line-of-sight and non-line-of-sight transmissions is adopted for mmWave communication.By using tools from stochastic geometry,we develop an analytical framework to analyze various performance metrics in the downlink hybrid HCNets under biased received power association.For UE clustering we considered Thomas cluster process and derive expressions for the association probability,coverage probability,area spectral efficiency,and energy efficiency.We also provide Monte Carlo simulation results to validate the accuracy of the derived expressions.Furthermore,we analyze the impact of mmWave operating frequency,antenna gain,small cell biasing,and BSs density to get useful engineering insights into the performance of hybrid mmWave HCNets.Our results show that network performance is significantly improved by deploying millimeter wave SBS instead of microwave BS in hot spots.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    Energy efficiency aware dynamic rate and power adaptation in carrier sensing based WLANs under Rayleigh fading and shadowing

    Forkan Uddin
    918-933页
    查看更多>>摘要：We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and trans-mission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction meth-odology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75％and 103％,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.
      原文链接:
    • NETL
    • NSTL
    • 万方数据