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EVchain: An Anonymous Blockchain-Based System for Charging–Connected Electric Vehicles

Tsinghua science and technology 2021年第6期26卷 845-856页

作者： Shiyuan Xu Xue Chen Yunhua He North China University of technology Beijing 100144China Beijing Key Laboratory of internet of things Security Institute of Information EngineeringChinese Academy of Sciences(CAS)Beijing 100093China

Purchases of electric vehicles have been increasing in recent years. These vehicles differ from traditional fossil-fuel-based vehicles especially in the time consumed to keep them running. Electric-Vehicle-charging Service Providers(EVSPs) must arrange reasonable charging times for users in advance. Most EVSP services are based on third-party platforms, but reliance on third-party platforms creates a lack of security, leaving users vulnerable to attacks and user-privacy leakages. In this paper, we propose an anonymous blockchain-based system for charging-connected electric vehicles that eliminates third-party platforms through blockchain technology and the establishment of a multi-party security system between electric vehicles and EVSPs. In our proposed system, digital certificates are obtained by completing distributed Public Key Infrastructure(distributed-PKI) identity registration,with the user registration kept separate from the verification process, which eliminates dependence on the EVSP for information security. In the verification process, we adopt smart contracts to solve problems associated with centralized verification and opaque services. Furthermore, we utilize zero-knowledge proof and ring-signature superposition to realize completely anonymous verification, which ensures undeniability and unforgeability with no detriment to anonymity. The evaluation results show that the user anonymity, information authenticity, and system security of our system fulfill the necessary requirements.

关键词： blockchain Electric Vehicles(EV) zero knowledge proof distributed Public Key Infrastructure(distributed-PKI) ring signature smart contract

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Using full duplex relaying in device-to-device(D2D)based wireless multicast services:a two-user case

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science China(Information sciences) 2015年第8期58卷 6-12页

作者： ZHANG GuoPeng YANG Kun LIU Peng DU Yao internet of things Research Center China University of Mining and Technology School of Computer science and Electronic Engineering University of Essex School of Information and Electrical Engineering China University of Mining and Technology

D2D communication has been proposed as an important supplement to the existing centralized cellular networks which allows two physically adjacent cellular user equipments(UEs) to communicate *** paper concerns using D2 D to improve wireless multicast services in cellular networks. Specially, we consider a D2 D transmitter UE can act as a full-duplex(FD) relay to assist a cellular multicast from a base station(BS) to a group of two UEs. And a new scheme which allows an intra-cell D2 D retransmission to underlay a cellular multicast is proposed. Under the constraint of the minimum signal-to-interference-and-noise ratio(SINR) required by each of the receiver UEs, the aim of the scheme is to select the best UE in a multicast group to perform the D2 D retransmission with the serving BS. Thus, the aggregate transmit power consumed at the BS and at the selected UE can be minimized. The numerical results show that the proposed scheme outperforms traditional cellular multicast scheme as it consumes less transmit power to achieve the same SINR target at the receiver UEs.

关键词： D2D communication cellular multicast full-duplex relaying power control interference management

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Orthogonal resource sharing scheme for device-to-device communication overlaying cellular networks: a cooperative relay based approach

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science China(Information sciences) 2015年第10期58卷 70-78页

作者： ZHANG GuoPeng LIU Peng YANG Kun DU Yao HU YanJun internet of things Research Center China University of Mining and Technology School of Computer science and Electronic Engineering University of Essex School of Information and Electrical Engineering China University of Mining and Technology

In this paper, we propose a device-to-device(D2D) communication scheme to improve local services in cellular networks. By employing cooperative relay(CR) technology, D2 D and cellular communications can operate in orthogonal resource sharing(ORS) mode with the aim of optimizing the data rates for local D2 D users while fulfilling the minimum rate requirements for prioritized cellular users. In the proposed CR-based ORS scheme, we consider a cellular communication that is willing to share part of the occupied bandwidth resource with some D2 D communications. Hence, the newly-obtained resource can be used by a D2 D communication for the following two purposes, i.e., to compensate the rate loss of the cellular communication through cooperative relaying and to communicate its own information so as to increase its own rate. We formulated this CR-based ORS problem as a non-convex optimization problem. Hence, a global maximizer may not exist for the *** find the optimal solution for the problem, an effective heuristic algorithm is developed. Simulation results show that the proposed D2 D communication scheme can significantly increase the rates of local D2 D users and also fulfill the minimum rate requirements of cellular users.

关键词： cellular networks D2D communication cooperative relay orthogonal resource sharing overlay

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Two-Stage Client Selection Scheme for Blockchain-Enabled Federated Learning in IoT

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Computers, Materials & Continua 2024年第11期81卷 2317-2336页

作者： Xiaojun Jin Chao Ma Song Luo Pengyi Zeng Yifei Wei Beijing Key Laboratory of Work Safety Intelligent Monitoring School of Electronic EngineeringBeijing University of Posts and TelecommunicationsBeijing100876China Institute of Industrial internet and internet of things China Academy of Information and Communications TechnologyBeijing100191China

Federated learning enables data owners in the internet of things(IoT)to collaborate in training models without sharing private data,creating new business opportunities for building a data ***,in practical operation,there are still some problems with federated learning *** has the characteristics of decentralization,distribution,and *** blockchain-enabled federated learning further improve the security and performance of model training,while also expanding the application scope of federated *** has natural financial attributes that help establish a federated learning data ***,the data of federated learning tasks may be distributed across a large number of resource-constrained IoT devices,which have different computing,communication,and storage resources,and the data quality of each device may also ***,how to effectively select the clients with the data required for federated learning task is a research *** this paper,a two-stage client selection scheme for blockchain-enabled federated learning is proposed,which first selects clients that satisfy federated learning task through attribute-based encryption,protecting the attribute privacy of *** blockchain nodes select some clients for local model aggregation by proximal policy optimization *** show that the model performance of our two-stage client selection scheme is higher than that of other client selection algorithms when some clients are offline and the data quality is poor.

关键词： Blockchain federated learning attribute-based encryption client selection proximal policy optimization

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An Improved Kalman Filter Positioning Method in NLOS Environment

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China Communications 2019年第12期16卷 84-99页

作者： Zhanjun Hao Beibei Li Xiaochao Dang College of Computer science and Engineering Northwest Normal UniversityLanzhou 730070China Gansu Province internet of things Engineering Research Center Lanzhou 730070China

In the precision positioning system, NLOS(Non Line of Sight) propagation and clock synchronization error caused by multiple base stations are the main reasons for reducing the reliability of communication and positioning accuracy. So, in the NLOS environment, it has an important role to eliminate the clock synchronization problem in the positioning system. In order to solve this problem, this paper proposes an improved Kalman filter localization method NLOS-K(Non Line of Sight-Kalman filter). First, the maximum likelihood estimation algorithm is used to iterate. Then, the Kalman filter algorithm is implemented and the Kalman gain matrix is redefined. The clock drift is compensated so that the clock between the master and slave base stations remains synchronized. The experimental results show that in the non-lineof-sight environment, compared with other algorithms, the positioning accuracy error of the improved algorithm is about 5 cm, and the accuracy compared with other algorithms is 97%. In addition, the influence of bandwidth and spectral density on the method is analyzed, and the accuracy and stability of positioning are improved as a whole.

关键词： NLOS clock synchronization Kalman filtering maximum likelihood estimation spectral density

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HgaNets:Fusion of Visual Data and Skeletal Heatmap for Human Gesture Action Recognition

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Computers, Materials & Continua 2024年第4期79卷 1089-1103页

作者： Wuyan Liang Xiaolong Xu School of internet of things Nanjing University of Posts and TelecommunicationsNanjing210023China School of Computer science Nanjing University of Posts and TelecommunicationsNanjing210023China

Recognition of human gesture actions is a challenging issue due to the complex patterns in both visual andskeletal features. Existing gesture action recognition (GAR) methods typically analyze visual and skeletal data,failing to meet the demands of various scenarios. Furthermore, multi-modal approaches lack the versatility toefficiently process both uniformand disparate input ***, in this paper, an attention-enhanced pseudo-3Dresidual model is proposed to address the GAR problem, called HgaNets. This model comprises two independentcomponents designed formodeling visual RGB (red, green and blue) images and 3Dskeletal heatmaps, *** specifically, each component consists of two main parts: 1) a multi-dimensional attention module forcapturing important spatial, temporal and feature information in human gestures;2) a spatiotemporal convolutionmodule that utilizes pseudo-3D residual convolution to characterize spatiotemporal features of gestures. Then,the output weights of the two components are fused to generate the recognition results. Finally, we conductedexperiments on four datasets to assess the efficiency of the proposed model. The results show that the accuracy onfour datasets reaches 85.40%, 91.91%, 94.70%, and 95.30%, respectively, as well as the inference time is 0.54 s andthe parameters is 2.74M. These findings highlight that the proposed model outperforms other existing approachesin terms of recognition accuracy.

关键词： Gesture action recognition multi-dimensional attention pseudo-3D skeletal heatmap

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Efficiency of local minima and GLM techniques in sinkhole extraction from a LiDAR-based terrain model

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International Journal of Digital Earth 2019年第9期12卷 1067-1082页

作者： Péter Enyedi Melinda Pap Zoltán Kovács László Takács-Szilágyi Szilárd Szabó a Department of Physical Geography and Geoinformatics University of DebrecenDebrecenHungary internet of things Research Institute Eszterházy Károly University of Applied SciencesEgerHungary

The aim of this paper was to study reliable automated delineationpossibilities of karst sinkholes using a LiDAR-based digital terrain model(DTM) with pixel-based classifications. We applied two approaches toextract sinkholes: (1) general linear modeling (GLM) with morphometricindices derived from DTM;(2) and a local minima-based delineationusing only LiDAR DTM as the input layer. The outcome of the localminima was significantly different from the reference ones but found allthe sinkholes without previous knowledge of the area. The GLM-basedoutcome did not differ statistically from the reference. Results showedthat these approaches were efficient in detecting sinkholes based onLIDAR derivatives, and can be used for risk assessment and hazardpreparedness in karst areas: GLM had an overall accuracy of 89.5% andlocal minima had an accuracy of 92.3%;both methods identifiedsinkholes but also had commission errors, identifying depressions assinkholes.

关键词： Karst mapping sinkhole identification general linear model statistical evaluation sink fill

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Short-term load forecasting model based on gated recurrent unit and multi-head attention

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The Journal of China Universities of Posts and Telecommunications 2023年第3期30卷 25-31页

作者： Li Hao Zhang Linghua Tong Cheng Zhou Chenyang School of Communications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China School of internet of things Nanjing University of Posts and TelecommunicationsNanjing 210003China

Short-term load forecasting(STLF)plays a crucial role in the smart ***,it is challenging to capture the long-time dependence and the nonlinear relationship due to the comprehensive fluctuations of the electrical *** this paper,an STLF model based on gated recurrent unit and multi-head attention(GRU-MA)is proposed to address the aforementioned *** proposed model accommodates the time series and nonlinear relationship of load data through gated recurrent unit(GRU)and exploits multi-head attention(MA)to learn the decisive features and long-term ***,the proposed model is compared with the support vector regression(SVR)model,the recurrent neural network and multi-head attention(RNN-MA)model,the long short-term memory and multi-head attention(LSTM-MA)model,the GRU model,and the temporal convolutional network(TCN)model using the public dataset of the Global Energy Forecasting Competition 2014(GEFCOM2014).The results demonstrate that the GRU-MA model has the best prediction accuracy.

关键词： deep learning short-term load forecasting(STLF) gated recurrent unit(GRU) multi-head attention(MA)

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Research on the Optimal Aggregation Method of Judgment Matrices Based on Spatial Steiner-Weber Point

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Journal of Systems science & Complexity 2023年第3期36卷 1228-1249页

作者： LIU Wei WANG Yuhong LI Lei School of internet of things Engineering Jiangnan UniversityWuxi 214122China School of Management Henan University of TechnologyZhengzhou 450001China School of Business Jiangnan UniversityWuxi 214122China

This paper is to provide a novel approach for the spatial aggregation of judgment *** optimal aggregation method of judgment matrices based on spatial Steiner-Weber point can effectively aggregate the preference information of group members and achieve the optimization of group *** method comprises three key elements:The spatial mapping of the judgment matrices,the spatial optimal aggregation model of the judgment matrices,and the plant growth simulation algorithm(PGSA)is used to find the optimal aggregation ***,the judgment matrices are mapped into a set of spatial multidimensional coordinates by using spatial mapping ***,the spatial Steiner-Weber point is used as the prototype to construct the spatial aggregation ***,the PGSA algorithm is used to find the spatial aggregation points,whose spatial weighted Euclidean distance to all the decision makers’preference points is *** optimal aggregation matrix is composed of these optimal aggregation points,which can accurately reflect the decision maker's comprehensive ***,the effectiveness and rationality of this method are verified by comparing with the classical group preference aggregation methods.

关键词： Aggregation method group decision making judgment matrices PGSA spatial aggregation model steiner-weber point

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Transmit Antenna Selection for Millimeter-Wave MIMO System Based on GBDT

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Journal of Communications and Information Networks 2023年第1期8卷 71-79页

作者： Lijun Yang Qianyi Zhu Xinchao Ge Lin Guo School of internet of things Nanjing University of Posts and TelecommunicationsNanjing 210000China School of Modern Posts Nanjing University of Posts and TelecommunicationsNanjing 210000China.

In millimeter-wave multiple-input multipleoutput(MIMO)systems,transmit antenna selection(TAS)can be employed to reduce hardware complexity and energy consumption when the number of antennas becomes very ***,the traditional exhaustive search TAS tries all possible antenna combinations which causes high computational *** may limit its application in *** main advantage of machine learning(ML)lies in the capability of establishing underlying relations between system parameters and objective,hence being able to shift the computation burden of real-time processing to the offline training *** on this advantage,introducing ML to TAS is a promising way to tackle the high computational complexity *** the existing ML-based algorithms try to approach the optimal performance,there is still a large room for *** this paper,considering the secure transmission of the system,we model the TAS problem as a multi-class classification problem and propose an efficient antenna selection algorithm based on gradient boosting decision tree(GBDT),in which we consider the system security capacity and computational complexity as the optimization *** the one hand,the system security performance is improved because its achievable security capacity is close to the traditional exhaustive search *** the other hand,compared with the exhaustive search algorithm and existing ML-based algorithms,the training efficiency is significantly improved with the complexity O(N),where N is the number of transmitting *** addition,the performance of the proposed algorithm is evaluated in mmWave MIMO system by employing New York University simulator(NYUSIM)model,which is based on the real channel *** analysis show that the proposed GBDT-based scheme can effectively improve the system secrecy capacity and significantly reduce the computational complexity.

关键词： millimeter-wave massive MIMO GBDT antenna selection ML

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