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Chinese Control and Decision Conference, CCDC

作者： Xintong Wang Yibo Sun Xuan Wang Enliang Wang Zhixin Sun Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China School of Information Technology and Electrical Engineering The University of Queensland Brisbane Brisbane Australia

Traffic prediction is the basis for dynamic network services and resource optimization. Software Defined networking (SDN) provides a global view for network measurement and management, and a reliable way for network information collection and network traffic prediction. Recently, SDN traffic prediction model enabled by deep learning mainly focuses on mining the temporal correlation of traffic data, while the modeling of its spatial correlation remains to be explored. From the perspective of the problem, a novel Spatial-Temporal Residual Graph Convolutional network (STRGCN) model for SDN Traffic Matrix (TM) prediction is proposed. Combined with SDN network topology, TM prediction is defined as time series data prediction in non-Euclidean space. Temporal Gated-Conv Blocks are based on Gated Convolutional Layer, and Spatial Graph-Conv Blocks are based on Graph Convolutional network (GCN). Through identity mapping between Spatial-Temporal Conv Blocks, the deep spatial and temporal features extraction is implemented. Tested by TM data from CERNET and GÉANT datasets, the accuracy and the timely performance of our model are evaluated. Experimental results suggest that the general performance of STRGCN for TM prediction in SDN is superior to the current deep learning models.

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Adaptive Multi-Core Real- Time Scheduling Based on Reinforcement Learning

Adaptive Multi-Core Real- Time Scheduling Based on Reinforce...

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International Conference on Control and Automation (ICCA)

作者： Yonghui Liang Hui Li Fei Shen Qimin Xu Shuna Hua Shanying Zhu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Re-search Center of Intelligent Control and Management Shanghai China Key Laboratory of Wireless Sensor Network and Communications Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China North Information Control Research Academy Group Company Ltd. Nanjing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

With the transformation towards industrial intel-ligence, multi-core processors are increasingly being applied in real-time networked control systems to ensure secure exe-cution of sensing, computing and actuating tasks under time constraints. However, existing scheduling methods result in either low CPU utilization or many missed task deadlines in dynamic systems. In this paper, we propose a two-layer scheduling architecture to address this issue by fully exploring the complex dependency between real-time tasks. To be specific, the local layer determines task execution priorities considering both dependency between tasks and deadline constraints by utilizing a reinforcement learning approach. Moreover, to better utilize the parallel capabilities of multi-core processors and reduce temporal collisions, this paper minimizes the requested core count for the task set based on a greedy strategy. The global layer designs a scheduling algorithm based on the pre-empt method and provides schedulability analysis of multiple task sets. Experimental results validate the correctness of the proposed scheduling approach, and efficiency is demonstrated through comparisons with baseline method.

关键词： Job shop scheduling Multicore processing Scheduling algorithms networked control systems Reinforcement learning Real-time systems sensors

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Design of Safety Monitoring System for Electrical Laboratory in Colleges and Universities under the Background of Informatization

Design of Safety Monitoring System for Electrical Laboratory...

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Advances in Informatics, Electronics and Education (ISAIEE), International Symposium on

作者： Huahui Liu Juan Liu Xusheng Hu Ma'anshan Engineering Technology Research Center for Wireless Sensor Network and Intellisense Ma'anshan China Key Laboratory of Unmanned Aerial Vehicle Development Data Application of Anhui Higher Education Institutes Wanjiang University of Technology Ma'anshan China Ma'anshan Technical College Ma'anshan China

ISBN: (纸本)9781665478755

With the development of economic globalization, information technology has made great progress, and artificial intelligence technology has been widely used, such as car driving, robot automatic steering, rescue and disaster relief robot, underwater robot and so on. However, in the laboratory management of colleges and universities, the application of artificial intelligence is insufficient, and the traditional management mode is backward. Some universities still adopt manual management mode, which not only has high labor cost, but also has a large management gap, resulting in too many potential safety hazards, which is not conducive to the safety management of university laboratories. The market urgently needs to realize the combination of laboratory management and artificial intelligence. As a Key Laboratory of engineering, the electrical laboratory carries out and sets up multiple experimental courses according to the discipline training requirements. As an engineering University, the course content spans multiple grades, faces more students and covers multiple majors in two colleges. It can be imagined that the experimental courses opened in the electrical laboratory basically take the power supply as the carrier, in this way, the requirements for students are very high. If the electrical experiment is misoperated or caused by emergencies, the risk is great and the accidents are very sudden. Based on the above situation, it fully shows that higher requirements are put forward for the safety management of the electrical laboratory and the management will be more difficult. In recent years, discipline construction has been paid more and more attention, but with the frequent occurrence of laboratory accidents, the fire safety related to the laboratory has attracted more and more attention. For the application-oriented laboratory in Colleges and universities, we must raise awareness, strengthen safety prevention, and strengthen the management of laboratory fire safet

关键词： Buildings Safety management Process control Control systems Software Safety Artificial intelligence

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LQR Control Method based on Improved Antlion Algorithm

LQR Control Method based on Improved Antlion Algorithm

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Chinese Control Conference (CCC)

作者： Zhe Sun Zhi Wen Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

In the face of the increasing demand of crane transportation speed and stability, an improved Ant-lion algorithm is proposed in this paper. On the original basis, the quasi-reverse learning method is used to improve the stability of the algorithm and make the initial data distributed evenly. Furthermore, an elite ant-lion growth mechanism is introduced to accelerate the convergence speed of the simulation and improve the simulation accuracy. Finally, the proposed algorithm is verified in the double pendulum system of crane based on LQR controller, and the feasibility and effectiveness of the proposed algorithm are proved by experiments.

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A WOA Based Switching PID Control for Overhead Crane

A WOA Based Switching PID Control for Overhead Crane

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Chinese Control Conference (CCC)

作者： Haoyong Yu Zhe Sun Yuhua Xu Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

Aiming at the problem that the amplitude of load oscillation is not easy to control in the movement process of overhead crane, this paper designs a switching PID control method based on whale optimization algorithm(WOA) to improve the performance of position control and anti-swing control for overhead crane. WOA is used to better adjust the parameters of PID controllers. The switching control is realized by a switching module, which defaults to the output of the Position PID Controller to provide control force for the trolley. When the absolute value of the load swing angle fed back by the crane system exceeds the warning value, the switching module immediately blocks the output of the Position PID Controller, and uses the Angle PID Controller to determine the control force. In addition, through theoretical analysis and simulation experiments under different conditions, the results verify the effectiveness of the WOA based switching control in position control and anti-swing control for overhead crane. Improve the efficiency and safety of overhead crane in practical industrial applications.

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Reference-Frame-Independent Measurement-Device-Independent Quantum Key Distribution Over 200 km of Optical Fiber

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Physical Review Applied 2021年第6期15卷 064016-064016页

作者： Xing-Yu Zhou Hua-Jian Ding Ming-Shuo Sun Si-Hao Zhang Jing-Yang Liu Chun-Hui Zhang Jian Li Qin Wang Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing 210003 China Broadband Wireless Communication and Sensor Network Technology Key Lab of Ministry of Education NUPT Nanjing 210003 China Telecommunication and Networks National Engineering Research Center NUPT Nanjing 210003 China

Reference-frame-independent (RFI) measurement-device-independent (MDI) quantum key distribution (QKD) is immune to all detector side-channel attacks and is insensitive to slow drifts of reference frames; thus, it is a promising candidate for the realization of long-distance quantum secure communications. However, its practical performance is predominantly limited by the finite-data-size effect compared with standard MDI QKD. By combining the collective constraint and joint-study strategy with our parameter estimation processes for the RFI-MDI-QKD protocol, we reduce the influence of the finite-data-size effect and substantially improve the protocol’s performance under realistic experimental conditions. Furthermore, a proof-of-principle experimental demonstration is conducted, and a transmission distance of up to 200 km is achieved. Therefore, this study represents a further step toward long-distance quantum secure communications.

关键词： Optical quantum information processing Quantum communication Quantum cryptography Quantum protocols Optical fibers Technological networks

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Value of Information-Based Packet Scheduling for AUV-Assisted UASNs

Value of Information-Based Packet Scheduling for AUV-Assiste...

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IEEE International Conference on Communications (ICC)

作者： Xiaoxiao Zhuo Wen Wu Liang Tang Fengzhong Qu Xuemin Shen Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Key Laboratory of Wireless Sensor Network and Communications SIMIT CAS Shanghai China Peng Cheng Laboratory Frontier Research Center Shenzhen China Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhejiang University Zhoushan China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

This paper studies autonomous underwater vehicles (AUV)-assisted underwater acoustic sensor networks (UASNs), where AUVs act as mobile sensor nodes to collect information from areas not accessible to static nodes and then relay data via static nodes. Due to the difficulty of obtaining the accurate global information of all the static nodes, we propose a novel packet scheduling scheme by utilizing local information obtained by AUVs. In the proposed scheme, the localization of static nodes stage and the topology construction stage are carried out beforehand to obtain the local information, based on which the transmission scheduling stage is implemented. Furthermore, in the transmission scheduling stage, we design a value of information (VoI)-based packet transmission scheduling (VBPS) strategy to avoid packet collision. Specifically, we introduce a performance metric, i.e., VoI, to measure the importance of data packets with different levels of urgency. Then, we formulate a combinatorial optimization problem to maximize VoI taking packet collision avoidance into consideration. A low-complexity distributed search algorithm is proposed to solve the problem, which exploits the spatial-temporal reuse to establish data packet collision constraints and then determines the next-hop node and data transmission time for AUVs. Extensive simulations under various scenarios are carried out to evaluate the performance of the proposed algorithm.

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Reference-frame-independent measurement-device-independent quantum key distribution using fewer states

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Physical Review A 2021年第2期103卷 022602-022602页

作者： Jing-Yang Liu Xing-Yu Zhou Qin Wang Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing 210003 China Broadband Wireless Communication and Sensor Network Technology Key Laboratory of Ministry of Education Ministry of Education Nanjing 210003 China Telecommunication and Networks National Engineering Research Center NUPT Nanjing 210003 China

Reference-frame-independent measurement-device-independent quantum key distribution (RFI-MDI-QKD) is immune to both detector side channel attacks and slow drifts of reference frames, and thus possesses a high level of security. In the traditional protocol of RFI-MDI-QKD, each legitimate user, Alice or Bob, has to prepare six encoding states in three orthogonal bases (X, Y, and Z), which are sent to the untrusted third party, Charlie. Then all the successful counting events are utilized for parameter estimations, which suffer from a severe finite-size effect. In this paper, we propose a scheme on RFI-MDI-QKD with fewer states and demonstrate that it can be secured and made useful by utilizing semidefinite programming. Numerical simulation results reveal the equivalence between those groups of different monitoring states from Alice and Bob. In addition, when considering practical experimental conditions and taking finite-size effects into account, our proposal can achieve a better performance than the traditional six-state RFI-MDI scheme, which provides a resource-saving and simpler state-preparation approach for practical implementations without sacrificing key rates.

关键词： Quantum communication Quantum cryptography

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research on the Loading Method of Logistics Vehicle and Cargo Based on IPSO Algorithm

Research on the Loading Method of Logistics Vehicle and Carg...

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Chinese Control Conference (CCC)

作者： Zewei Zhao Huqing Wang Zhe Sun Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing P. R. China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

Logistics vehicle and cargo matching problem is a typical combination optimization problem, which has important theoretical and application value in the field of logistics distribution. The proved particle swarm optimization (PSO) algorithm is one of the most extensive optimization methods studied in recent years, with excellent global search ability and convergence speed. Based on the IPSO algorithm, this paper proposes an effective IPSO algorithm model for the matching problem of logistics vehicles and goods, and conducts the corresponding comparative experiment. The final experimental results show that the algorithm has good results in practical application and can provide a feasible optimization method for solving the problem of logistics vehicles and goods.

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Efficient Object Detection Method Based on Improved YOLOv3 network for Remote Sensing Images

Efficient Object Detection Method Based on Improved YOLOv3 N...

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International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Jintao Wang Wen Xiao Tianwei Ni Key Laboratory of Unmanned Aerial Vehicle Development & Data Application of Anhui Higher Education Institutes Maanshan China Wanjiang University of Technology Maanshan Wireless Sensor Network and Intelligent Perception Engineering Technology Research Center Maanshan China Wanjiang University of Technology Maanshan China

ISBN: (数字)9781728197418

ISBN: (纸本)9781728197425

In the future, Drones or general Unmanned Aerial Vehicles(UAVs) need to implement online real-time object detection, but their memory and computing power are limited. An improved YOLOv3 is adopted in this paper, making full use of the lightweight network instead of the feature extraction network of YOLOv3 to achieve high-efficiency object detection for remote sensing images. In the case of similar detection accuracy, parameters and FLOPs (floating point operations) of the improved model are 2.5 times and 3.3 times smaller than YOLOv3, respectively. In addition, an IoU K-medians algorithm is proposed, which improves mAP by 7.0% on YOLOv3 and by 2.3% on the improved *** show that the detection speed of the improved YOLOv3 is 101 frame/s at the fastest, and it is still 1.6 times faster than that of YOLOv3 when its mAP is 6% higher than that of YOLOv3. The efficient remote sensing object detection method proposed in this paper lays the foundation for future UAVs.

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