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Wenjiang Ji

Bio: Wenjiang Ji is an academic researcher from Xi'an University of Science and Technology. The author has contributed to research in topics: Cloud computing & Computer science. The author has an hindex of 6, co-authored 46 publications receiving 137 citations. Previous affiliations of Wenjiang Ji include Civil Aviation University of China.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: Experimental results demonstrate that the proposed CNN-LSTM method is more accurate and features a shorter time cost, which meets the prediction requirements and provides an effective method for the safe operation of unmanned systems.
Abstract: Accurate monitoring the surrounding environment is an important research direction in the field of unmanned systems such as bio-robotics, and has attracted much research attention in recent years. The trajectories of surrounding vehicles should be predicted accurately in space and time to realize active defense and running safety of an unmanned system. However, there is uncertainty and uncontrollability in the process of trajectory prediction of surrounding obstacles. In this study, we propose a trajectory prediction method based on a sequential model, that fuses two neural networks of a convolutional neural network (CNN) and a long short-term memory network (LSTM). First, a box plot is used to detect and eliminate abnormal values of vehicle trajectories, and valid trajectory data are obtained. Second, the trajectories of surrounding vehicles are predicted by merging the characteristics of CNN space expansion and LSTM time expansion; the hyper-parameters of the model are optimized according to a grid search algorithm, which satisfies the double-precision prediction requirement in space and time. Finally, data from next generation simulation (NGSIM) and Creteil roundabout in France are taken as test cases; the correctness and rationality of the method are verified by prediction error indicators. Experimental results demonstrate that the proposed CNN-LSTM method is more accurate and features a shorter time cost, which meets the prediction requirements and provides an effective method for the safe operation of unmanned systems.

82 citations

Journal ArticleDOI
TL;DR: This paper considers cheating problem in bivariate polynomial based secret sharing scheme, and proposes two cheating identification algorithms respectively that are efficient with respect of cheater identification capabilities and achieves stronger capability of cheating identification with the collaboration of the rest n − m users who are not involved in secret reconstruction.

57 citations

Journal ArticleDOI
TL;DR: This article proposes a novel IoV block-streaming service awareness and trusted verification in 6 G, combined with identity-based blind signature technology, which can realize the mutual authentication of IoV devices and edge servers while keeping the user's real identity information confidential.
Abstract: 6 G and mobile Internet-of-Vehicles (IoV) technology require a secure, open, and transparent system. Blockchain has the characteristics of decentralization, non-tampering, and traceability, which can improve the robustness, data privacy, and security transparency of the overall system. Therefore, blockchain will be the most promising technology to ensure the security and privacy of 6 G and vehicle networks. In this article, we propose a novel IoV block-streaming service awareness and trusted verification in 6 G. The edge node uploads the microservices and calling diagram of microservices to the blockchain network. The blockchain network serves as an intermediate verification platform for the edge node and the IoV equipment to record the evidence of interaction between the two ends. Moreover, combined with identity-based blind signature technology, we have designed a security scheme in which IoV devices anonymously request services from edge nodes, which can realize the mutual authentication of IoV devices and edge servers while keeping the user's real identity information confidential. In addition, an edge caching mechanism based on user requests and service awareness is designed to pre-compile services at edge nodes, improve the cache hit rate of service requests from vehicle users on the edge server, and achieve efficient processing of resource requests from users.

23 citations

Journal ArticleDOI
01 Dec 2016
TL;DR: A virtual machine placement optimization model based on optimized ant colony algorithm is proposed, able to determine the physical machines suitable for hosting migrated virtual machines and solves the problem of redundant power consumption resulting from idle resource waste of physical machines.
Abstract: A virtual machine placement optimization model based on optimized ant colony algorithm is proposed. The model is able to determine the physical machines suitable for hosting migrated virtual machines. Thus, it solves the problem of redundant power consumption resulting from idle resource waste of physical machines. First, based on the utilization parameters of the virtual machine, idle resources and energy consumption models are proposed. The models are dedicated to quantifying the features of virtual resource utilization and energy consumption of physical machines. Next, a multi-objective optimization strategy is derived for virtual machine placement in cloud environments. Finally, an optimal virtual machines placement scheme is determined based on feature metrics, multi-objective optimization, and the ant colony algorithm. Experimental results indicate that compared with the traditional genetic algorithms-based MGGA model, the convergence rate is increased by 16%, and the optimized highest average energy consumption is reduced by 18%. The model exhibits advantages in terms of algorithm efficiency and efficacy.

17 citations

Journal ArticleDOI
TL;DR: A novel game theory-based model is proposed to describe the scenario, in which the botmaster launching Distributed Denial of Service attacks using a botnet while the defender equipped a firewall defending, and it is helpful to evaluate defense ability of the defender towards current botmaster attacks by analyzing attack log in sandbox.
Abstract: Botnet has become a popular technique for deploying Internet crimes. The command of botnet has evolved into a major way for attackers to launch Distributed Denial of Service attacks on network servers. Modelized analysis methods need to be studied for botnet attacks implements, defense, and prediction. In this paper, we propose a novel game theory-based model to describe the scenario, in which the botmaster launching Distributed Denial of Service attacks using a botnet while the defender equipped a firewall defending. In our model, we consider the following: firstly, the botmaster and the defender can be rational or irrational; secondly, the interaction between the botmaster and the defender is modeled as a dynamic game; thirdly, their supporting or not self-learning databases. We detail the analysis of eight sub-scenarios for the assumptions and give an easy-to-use algorithm for adjustment of offensive and defensive strategy. We use the OPNET to validate our model and its effectiveness. The experiment result shows that our strategy can improve the firewall abilities to lower false alarm rate FR and improve the botmaster lower exposure rate of botnet to avoid detection. Furthermore, the model is helpful to evaluate defense ability of the defender towards current botmaster attacks by analyzing attack log in sandbox. Copyright © 2016 John Wiley & Sons, Ltd.

14 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, a boundary control approach is used to control a two-link rigid-flexible wing, which is based on the principle of bionics to improve the mobility and the flexibility of aircraft.
Abstract: A boundary control approach is used to control a two-link rigid-flexible wing in this article. Its design is based on the principle of bionics to improve the mobility and the flexibility of aircraft. First, a series of partial differential equations (PDEs) and ordinary differential equations (ODEs) are derived through the Hamilton's principle. These PDEs and ODEs describe the governing equations and the boundary conditions of the system, respectively. Then, a control strategy is developed to achieve the objectives including restraining the vibrations in bending and twisting deflections of the flexible link of the wing and achieving the desired angular position of the wing. By using Lyapunov's direct method, the wing system is proven to be stable. The numerical simulations are carried out with the finite difference method to prove the effectiveness of designed boundary controllers.

245 citations

Journal ArticleDOI
TL;DR: A review on the ML-based computation offloading mechanisms in the MEC environment in the form of a classical taxonomy to identify the contemporary mechanisms on this crucial topic and to offer open issues as well.

172 citations

Journal ArticleDOI
TL;DR: It is proved that all states of the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB) by utilizing the Lyapunov stability principles.
Abstract: In this article, an admittance-based controller for physical human–robot interaction (pHRI) is presented to perform the coordinated operation in the constrained task space. An admittance model and a soft saturation function are employed to generate a differentiable reference trajectory to ensure that the end-effector motion of the manipulator complies with the human operation and avoids collision with surroundings. Then, an adaptive neural network (NN) controller involving integral barrier Lyapunov function (IBLF) is designed to deal with tracking issues. Meanwhile, the controller can guarantee the end-effector of the manipulator limited in the constrained task space. A learning method based on the radial basis function NN (RBFNN) is involved in controller design to compensate for the dynamic uncertainties and improve tracking performance. The IBLF method is provided to prevent violations of the constrained task space. We prove that all states of the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB) by utilizing the Lyapunov stability principles. At last, the effectiveness of the proposed algorithm is verified on a Baxter robot experiment platform. Note to Practitioners —This work is motivated by the neglect of safety in existing controller design in physical human–robot interaction (pHRI), which exists in industry and services, such as assembly and medical care. It is considerably required in the controller design for rigorously handling constraints. Therefore, in this article, we propose a novel admittance-based human–robot interaction controller. The developed controller has the following functionalities: 1) ensuring reference trajectory remaining in the constrained task space: a differentiable reference trajectory is shaped by the desired admittance model and a soft saturation function; 2) solving uncertainties of robotic dynamics: a learning approach based on radial basis function neural network (RBFNN) is involved in controller design; and 3) ensuring the end-effector of the manipulator remaining in the constrained task space: different from other barrier Lyapunov function (BLF), integral BLF (IBLF) is proposed to constrain system output directly rather than tracking error, which may be more convenient for controller designers. The controller can be potentially applied in many areas. First, it can be used in the rehabilitation robot to avoid injuring the patient by limiting the motion. Second, it can ensure the end-effector of the industrial manipulator in a prescribed task region. In some industrial tasks, dangerous or damageable tools are mounted on the end-effector, and it will hurt humans and bring damage to the robot when the end-effector is out of the prescribed task region. Third, it may bring a new idea to the designed controller for avoiding collisions in pHRI when collisions occur in the prescribed trajectory of end-effector.

170 citations

Journal ArticleDOI
TL;DR: The control design and experiment validation of a flexible two-link manipulator (FTLM) system represented by ordinary differential equations (ODEs) are discussed and a reinforcement learning (RL) control strategy is developed that is based on actor–critic structure to enable vibration suppression while retaining trajectory tracking.
Abstract: This article discusses the control design and experiment validation of a flexible two-link manipulator (FTLM) system represented by ordinary differential equations (ODEs). A reinforcement learning (RL) control strategy is developed that is based on actor–critic structure to enable vibration suppression while retaining trajectory tracking. Subsequently, the closed-loop system with the proposed RL control algorithm is proved to be semi-global uniform ultimate bounded (SGUUB) by Lyapunov’s direct method. In the simulations, the control approach presented has been tested on the discretized ODE dynamic model and the analytical claims have been justified under the existence of uncertainty. Eventually, a series of experiments in a Quanser laboratory platform are investigated to demonstrate the effectiveness of the presented control and its application effect is compared with PD control.

136 citations

Journal ArticleDOI
TL;DR: In this article, an adaptive fault tolerant control strategy is developed to suppress the vibrations of the flexible panel in the course of the attitude stabilization, and a Lyapunov-based stability analysis is conducted to determine whether the system energies, angular velocities and transverse deflections, remain bounded and asymptotically decay to zero in the case of infinite number of actuator failures.
Abstract: In this paper, we address simultaneous control of a flexible spacecraft’s attitude and vibrations in a three-dimensional space under input disturbances and unknown actuator failures. Using Hamilton’s principle, the system dynamics is modeled as an infinite dimensional system captured using partial differential equations. Moreover, a novel adaptive fault tolerant control strategy is developed to suppress the vibrations of the flexible panel in the course of the attitude stabilization. To determine whether the system energies, angular velocities and transverse deflections, remain bounded and asymptotically decay to zero in the case wherein the number of actuator failures is infinite, a Lyapunov-based stability analysis is conducted. Finally, extensive numerical simulations are performed to demonstrate the performance of the proposed adaptive control strategy.

103 citations