Trajectory-prediction based relay scheme for time-sensitive data communication in VANETs

( Zilong Jin ),( Yuxin Xu ),( Xiaorui Zhang ),( Jin Wang ),( Lejun Zhang ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.8

In the Vehicular Ad-hoc Network (VANET), the data transmission of time-sensitive applications requires low latency, such as accident warnings, driving guidance, etc. However, frequent changes of topology in VANET will result in data transmission failures. In order to improve the efficiency of VANETs data transmission and increase the timeliness of data, this paper proposes a relay scheme based on Recurrent Neural Network (RNN) trajectory prediction, which can be used to select the optimal relay vehicle to transmit data. The proposed scheme learns vehicle trajectory in a distributed manner and calculates the predicted trajectory, and then the optimal vehicle can be selected to complete the data transmission, which ensures the timeliness of the data. Finally, we carry out a set of simulations to demonstrate the performance of the algorithm. Simulation results show that the proposed scheme enhances the timeliness of the data and the accuracy of the predicted driving trajectory.

A Context-aware Task Offloading Scheme in Collaborative Vehicular Edge Computing Systems

( Zilong Jin ),( Chengbo Zhang ),( Guanzhe Zhao ),( Yuanfeng Jin ),( Lejun Zhang ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.2

With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.

Dynamic Analyses and Simplified Methods for Evaluating Complicated Suspend-dome Structures Subjected to Sudden Cable Failure

Chao Zhang,Zhichao Lai,Xiaoqiang Yang,Qiang Li,Zilong Zhang,Xindi Fu 한국강구조학회 2023 International Journal of Steel Structures Vol.23 No.1

Accidental cable failure may occur for complicated suspend-dome structures, resulting in the dynamic impact effect on structures. This study presents simplified analysis methods for evaluating suspend-dome structures when sudden cable failure occurs. An implicit analysis method of improved alternative load path (IAM-IAP) was employed to simply simulate the cable failure process of the beam-string structure. The IAM-IAP was also validated by comparing the calculated results with the existing test results for the truss string structure. The parameters of the cable failure process (i.e., failure time, failure path, and damping ratio) were analyzed, and suitable values were recommended. Based on the IAM-IAP, a finite element model of multi-loop cable-string suspend-dome structure (MCSS) was established and benchmarked by verifying the static responses during construction. Dynamic responses (i.e., time histories, displacements, axial forces, and dynamic amplification factors) of MCSS were systematically investigated. The dynamic amplification factor may be larger than 2, exceeding the suggested value of existing specifications. A static equivalent method with reasonable prediction accuracy was also proposed to simply assess the dynamic responses of suspend-dome structures subjected to sudden cable failure.

Optimizing Energy-Latency Tradeoff for Computation Offloading in SDIN-Enabled MEC-based IIoT

Xinchang Zhang,Changsen Xia,Tinghuai Ma,Lejun Zhang,Zilong Jin 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.12

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.

Data-Driven Quadratic Optimization for Tracking Problems with Application to a Tray Indexing System

Zilong Cheng,Jun Ma,Xiaocong Li,Xiaoxue Zhang,Tong Heng Lee 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10

Iterative Feedback Tuning (IFT) algorithm explores the correlation between the cost function and the parameters of the controller. It introduces one data-driven approach to derive the gradient of the cost function with respect to the controller parameters and provides an iterative numerical method for the controller parameters optimization. However, classical IFT algorithms require three experiments to be conducted at one iteration, and one special experiment is included in the three experiments. That means the reference signal is changed during the iteration because of the special experiment, which restricts the application of the IFT algorithm in many areas. Besides, in many process control applications with long duration, IFT algorithm is much more time-consuming than many other tuning algorithms. In this paper, a novel IFT algorithm is proposed. For each iteration, no special experiment is required, which means parameters of the controller can be tuned when the system is running normally. Simulation results on a tray indexing system demonstrate the high performance and applicability of this algorithm.

Semi-Proximal ADMM for Model Predictive Control Problem with Application to a UAV System

Zilong Cheng,Jun Ma,Xiaoxue Zhang,Tong Heng Lee 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10

A lasso model predictive control (MPC) problem solved by the alternative direction method of multipliers (ADMM) is investigated in this work. More specifically, a semi-proximal ADMM algorithm with Gauss-Seidel iterations is proposed to solve the lasso MPC problem with singular weighting matrices. It is well-known that the interior-point algorithm is an effective and efficient algorithm, which is commonly used to obtain the real-time solution to the MPC optimization problem. However, when the weighting matrices of the lasso MPC problem are singular, it is extremely challenging to solve the optimization problem by using the classical interior-point algorithm. In fact, in some special cases, the interior-point algorithm is entirely infeasible for solving the aforementioned problems. In the work here, our developments reveal that the proposed optimization methodology (a semi-proximal ADMM algorithm with Gauss-Seidel iterations) is much more advantageous compared to the interior-point algorithm in some specific cases, especially in the case where singular weighting matrices exist in the cost function. An MPC based tracking problem of an unmanned aerial vehicle (UAV) system is implemented to compare the performance of the proposed algorithm to the performance of the existing solver. The simulation result shows that with the proposed algorithm, higher accuracy and computational efficiency can be realized.

Transcriptome analysis for identifying possible causes of postreproductive death of Sepia esculenta based on brain tissue

Jinyong Zhang,Muchun He,Zilong Xiang,Shufang Liu,ZhiMeng Zhuang 한국유전학회 2019 Genes & Genomics Vol.41 No.6

Background The subpeduncle lobe/olfactory lobe–optic gland axis is called the endocrine regulation center of cephalopods. However, little is known about the mechanism of the subpeduncle lobe/olfactory lobe-optic gland axis regulate the sexual maturation and post-reproductive death of Sepia esculenta Hoyle. Objectives The primary objective of this study was to provide basic information for revealing the mechanism of the subpeduncle lobe/olfactory lobe–optic axis regulating the rapid post-reproductive death of S. esculenta. Methods In this paper, Illumina sequencing based transcriptome analysis was performed on the brain tissue of female S. esculenta in the three key developmental stages: growth stage (BG), spawning stage (BS), and post-reproductive death stage (BA). Results A total of 66.19 Gb Illumina sequencing data were obtained. A comparative analysis of the three stages showed 2609, 3333, and 170 differentially expressed genes (DEGs) in BG-vs-BA, BG-vs-BA, and BS-vs-BA, respectively. The Gene Ontology (GO) enrichment analysis of DEGs revealed that the regulation of cyclin-dependent protein serine/threonine kinase activity, oxidative phosphorylation, and respiratory chain were significantly enriched. The significant enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway identified pathways associated with the regulation of death, such as the mammalian target of rapamycin (mTOR) signaling pathway, AMPK signaling pathway, oxidative phosphorylation, and cell cycle. Conclusion The post-reproductive death of S. esculenta was found to be a complex energy steady-state regulation network system. The mTOR acted as an energy receptor and had a key role in regulating energy homeostasis.

A Collision-Free Framework for Navigation of Nonholonomic Vehicle Systems

Xiaoxue Zhang,Jun Ma,Zilong Cheng,Tong Heng Lee 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10

The task of highly effective navigation is certainly one of the critical technologies of autonomous vehicles that have been widely investigated by researchers. In this paper, a navigation framework with path planning and tracking is presented, where a feasible and collision-free trajectory is generated for nonholonomic vehicle systems. In terms of path planning, an LQR-RRT<SUP>*</SUP> algorithm is applied to plan a path without collision. It is an optimal sampling-based planning algorithm with linear quadratic regulation-based heuristics, and able to tackle some rather complicated or underactuated dynamic systems. In order to improve the feasibility of the planned path and compensate for the deterioration of optimality due to sampling times, the approach is taken where a cubic spline path is additionally generated. The path tracking problem is formulated as a constrained optimization problem for the nonholonomic vehicle system, and then the required steering angle and acceleration is computed to avoid potential collisions. The results of the simulation experiments clearly demonstrate the effectiveness of the proposed navigation framework.

Integrated Planning and Control for Collision-free Trajectory Generation in 3D Environment with Obstacles

Xiaoxue Zhang,Jun Ma,Sunan Huang,Zilong Cheng,Tong Heng Lee 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10

Control of autonomous robots (ARs) is a hot topic over the past three decades, and motion planning is becoming one of the major challenges in AR control. Substantial works have been done for motion planning in 2-dimensional (2D) environments, but planning in 3D complex environments is still an open problem to be investigated. In this paper, we propose a trajectory planning method to plan a high-quality and safe trajectory in 3-dimensional (3D) environments with multiple obstacles. The proposed method is based on the integration of a global optimal 3D path planner with a local planner. First, a hierarchical path planning algorithm is used as a global path planner to compute a near-optimal path formed by a set of waypoints. Second, a local path trajectory planner is designed to track the path computed by the global path planner with multiple constraints of dynamics and environment satisfied. Finally, simulations are conducted to validate the effectiveness of the proposed trajectory generation approach subject to the constraints of robot physical limits and environmental requirements.

Numerical study on the shock vector control performance in a de Laval nozzle with single or dual injection ports

Lite Zhang,Mengyu Su,Zilong Feng,Hao Guan,Haozhe Jin,Hong-Hui Shi 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.6

In this study, a comparison of five commonly used turbulence models was conducted in predictions of supersonic flows in a two-dimensional shock vector control nozzle. The result indicated that shear stress transport k-ω turbulence model performed best, and hence it was employed to carry out a parametric study on the shock wave vector control performance. The effects of slot interval distance, slot width, and injection angle on the deflection angle, thrust coefficient, and thrust efficiency were analyzed. All these performance parameters of a dual injection port nozzle can be better than those of a single injection port nozzle as long as the slot interval distance and width are appropriately selected. Under some investigated conditions, there exist an optimal slot interval distance and slot width both for the deflection angle and thrust efficiency, respectively.