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Delay Aware 6TiSCH Iiot Networks for Energy Efficient Data Transmission by Adopting Federated Learning and Edge Computing

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2024年第3期70卷 5911-5928页

作者： Rafiq, Ahsan Wei, Min Wang, Ping Kumar Jain, Deepak Chongqing Univ Posts & Telecommun Automat Sch Key Lab Ind IoT & Networked ControlMinist Educ China Korea Belt & Rd Joint Lab Ind Internet Thing Chongqing 400065 Peoples R China Dalian Univ Technol Sch Artificial Intelligence Dalian 116024 Peoples R China

Standardizing the industrial Internet of Things (Iiot) with 6TiSCH enables the Iiot nodes to utilize low power with high reliability. It ensures the allocation of resources for Iiot nodes with minimal power consumption. The existing work focused on various issues in the 6TiSCH-based Iiot in terms of network formation, and scheduling. However, security, energy efficiency, and latency remain challenging issues. The aforementioned issues are resolved by adopting different technologies in the 6TiSCH Iiot environment such as edge computing and federated learning named AIFed-6TiSCH Iiot. In the 6TiSCH layer, all Iiot nodes are authenticated to the Trusted Authority (TA) to reduce unwanted malicious traffic using Hybrid Authentication Algorithm (HAS) named Mchacha-poly 1305 algorithm based on several credentials. The authenticated nodes are allowed to form the network, for that we utilized a multicast CORONA-based DODAG structure using the Dijkstra algorithm. Eventually, new node joining is initiated by an already joined node which transmits Enhanced Beacons (EBs) in adaptive time intervals for synchronizing the new node. The synchronized nodes aim to select the optimal parent for transmitting data to the root node using an Enhanced Sea Gull (ESG) optimization algorithm based on mobility and several information. After that, optimal channel selection and scheduling are done using a Multi Criteria Decision Making (MCDM) algorithm named TOPSIS and a hybrid scheduling algorithm (i.e., Autonomous, and centralized scheduling) based on federated learning. By Performing channel selection, the congestion rate is reduced and federated learning ensures privacy and communication reliability. In the edge layer, data from the root are forwarded via a smart gateway to the edge servers for local processing. The security and latency issues in the edge layer are mitigated by performing Deep Reinforcement Learning (DRL) based migration named Enhanced Multi-Agent Deep Deterministic Policy Gra

关键词： industrial Internet of Things Energy consumption Synchronization Routing Task analysis Reliability Federated learning industrial Internet of Things (Iiot) 6TiSCH artificial intelligence (AI) edge computing federated learning (FL) hybrid scheduling and migration

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H2/H∞ control of AETSCP-Based IT-2 Fuzzy networked control Systems Under Stealthy Dos Attacks and Actuator Faults

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2025年第9期35卷 3791-3804页

作者： Zhu, Yunjiao Tang, Xiaoming Wang, Jun Zhai, Shidong Yuan, Jingjie She, Minghong Chongqing Univ Posts & Telecommun Key Lab Ind Internet Things & Networked Control Minist Educ Chongqing Peoples R China Chongqing Univ Posts & Telecommun Coll Automat Chongqing Peoples R China Chongqing Special Equipment Inspection & Res Inst Chongqing Peoples R China Mianyang Teachers Coll Sichuan Prov Key Lab IOT Secur Mianyang Peoples R China

This paper examines the dynamic output feedback H-2/H-infinity control of interval type-2 (IT-2) fuzzy systems suffering from stealthy denial of service (DoS) attacks under the adaptive event-triggered stochastic communication protocol (AETSCP). Considering the advantages of the AET mechanism and the SCP, a new AETSCP is proposed, whose trigger parameters can be dynamically adjusted based on the changing trend of the system state and the stealthy DoS attack probability. The signal-to-interference plus noise ratio (SINR)-based DoS attacker continuously senses the channel and utilizes the trigger characteristics of the AET mechanism to cleverly launch the attack to ensure its stealthiness. A dynamic quantizer is employed to quantize the measured output, and a time-varying fault matrix is adopted to represent actuator faults. By applying the mode-dependent Lyapunov function, the sufficient condition to ensure the stability of the considered networked control system (NCS) is derived, and the dynamic output feedback controller satisfying the H-2/H-infinity performance is designed. Lastly, a simulation example is used to verify the effectiveness of the proposed algorithm.

关键词： actuator faults adaptive event-triggered stochastic communication protocol (AETSCP) dynamic output feedback H-2/H-infinity performance stealthy denial of service (DoS) attacks

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A look into smart factory for industrial iot driven by SDN technology: A comprehensive survey of taxonomy, architectures, issues and future research orientations

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2024年第5期36卷

作者： Josbert, Nteziriza Nkerabahizi Wei, Min Wang, Ping Rafiq, Ahsan Chongqing Univ Posts & Telecommun Automat Sch Minist EducNatl Ind IoT Int S&T Cooperat Base Key Lab Ind IoT & Networked Control Chongqing Peoples R China

The Internet of Things (iot) provides a major contribution to the innovation of smart manufacturing and industrial automation. Due to iot, network devices and intelligent machines exchange information through different types of Internet connection and processes are predominantly automated. This reduces significantly the need for more human intervention and supports high performance. Nevertheless, the utilization of iot in industrial automation called industrial iot (Iiot) has several issues, including the management of applications and Iiot devices. Moreover, heterogeneous networks and tremendous devices deployed in the Iiot environment require flexible configuration and reconfiguration according to the change for ensuring dynamic performance. We argue that Software-Defined Networking (SDN) is one of the technologies that can be used to solve some of the previously mentioned issues. In this paper, we propose a survey for the implementation of SDN solutions in Iiot and discuss the pros and cons brought about by this synergy named "SDN-Iiot". We explore the current articles on SDN-Iiot by considering different crucial domains such as flow installation techniques, fault tolerance, traffic routing optimization, resource management, energy efficiency, real-time, and network security. Furthermore, we analyze Artificial Intelligence (AI)/Machine Learning (ML) tasks to improve the performance of SDN-Iiot and the deployment of different technologies like Network Function Virtualization (NFV) and Time-Sensitive Networking (TSN) in SDN-Iiot. After observing the limitations of existing SDNIiot architectures, we propose an improved candidate architecture for SDN-Iiot based on a hierarchical distributed control plane. The new SDN-Iiot architecture contains AI, industrial Backhaul Network (IBN), Dynamic Hash Table (DHT), AdaptFlow protocol, and edge/cloud storages. This paper selects the five most used SDN controllers by the literature review and identifies the features of each SD

关键词： Software-Defined Networking (SDN) industrial Internet of Things (Iiot) SDN-Iiot architecture Software-Defined industrial Network (SDIN) SDN solutions

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Rolling Bearing Fault Detection of Civil Aircraft Engine Based on Adaptive Estimation of Instantaneous Angular Speed

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IEEE TRANSACTIONS ON industrial INFORMATICS 2020年第7期16卷 4938-4948页

作者： Wang, Yi Tang, Baoping Qin, Yi Huang, Tao Chongqing Univ Coll Mech Engn State Key Lab Mech Transmiss Chongqing 400044 Peoples R China Minist Educ Ind IOT & Networked Control Key Lab Beijing Peoples R China

Diagnosis of a civil aircraft engine, which is operating under speed variation conditions, is a representative problem encountered in aeronautic industry. It is still very challenging to estimate the instantaneous angular speed (IAS) through the aircraft engine vibration signal when no encoder or tachometer is available due to cost or technological reasons. However, for the currently available tacholess order tracking algorithms, many vital parameters must be initialized manually in advance, which lead to user-friendliness, even false diagnosis. To address this issue, a novel method is proposed and the merits of nonlinear mode decomposition are inherited, so the IAS can be estimated adaptively without prior knowledge. The vibration signal collected from a civil aircraft engine is used for validation;the experimental results exhibit that the proposed method is more accurate and flexible when compared with the conventional methods.

关键词： Aircraft engine instantaneous angular speed (IAS) nonlinear mode decomposition (NMD) rolling bearing fault diagnosis tacholess order tracking (TLOT)

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Real-Time Acceleration-Continuous Path-Constrained Trajectory Planning With Built-In Tradeoff Between Cruise and Time-Optimal Motions

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2020年第4期17卷 1911-1924页

作者： Shen, Peiyao Zhang, Xuebo Fang, Yongchun Yuan, Mingxing Nankai Univ Tianjin Key Lab Intelligent Robot Inst Robot & Automat Informat Syst Tianjin 300071 Peoples R China Chongqing Univ Posts & Telecommun Minist Educ Key Lab Ind IoT & Networked Control Chongqing 400065 Peoples R China

In this article, a novel real-time acceleration-continuous path-constrained trajectory planning algorithm is proposed with an appealing built-in tradeoff mechanism between the cruise motion and time-optimal motion. Different from existing approaches, the proposed approach smoothens time-optimal trajectories with bang-bang input structures to generate acceleration-continuous trajectories while preserving the completeness property. More importantly, a novel built-in tradeoff mechanism is proposed and embedded into the trajectory planning framework so that the proportion of the cruise motion and time-optimal motion can be flexibly adjusted by changing a user-specified functional parameter. Thus, the user can easily apply the trajectory planning algorithm for various tasks with different requirements on motion efficiency and cruise proportion. Moreover, it is shown that feasible trajectories are computed more quickly than optimal trajectories. Rigorous mathematical analysis and proofs are presented for those aforementioned theoretical results. Comparative simulations and experimental results on an omnidirectional wheeled mobile robot demonstrate that flexible tunings between the cruise and time-optimal motions can be achieved in a higher computational efficiency manner by the proposed algorithm. Note to Practitioners-This article is motivated by the time-optimal and smooth motion planning problem for mobile robots along given paths. Existing approaches generally use the piecewise polynomial interpolations to smoothen and adjust feasible trajectories. This article proposes a novel path-constrained trajectory planning approach, which preserves properties of completeness and a high-efficient tradeoff mechanism between the optimal and cruise motions when achieving a globally optimal and acceleration-continuous trajectory. Comparative experimental results with other methods show the effectiveness of the proposed approach. In future research, we will attempt to integrate the

关键词： Trajectory Acceleration Trajectory planning Robots Planning Heuristic algorithms Real-time systems Cruise motion time optimality tradeoff mechanism trajectory planning

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IMPSO and Linear Programming-Based Energy-Efficient Cell Association Algorithm for Backhaul-Constrained Ultra-Dense Small-Cell Networks

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MATHEMATICAL PROBLEMS IN ENGINEERING 2021年第1期2021卷

作者： Jiang, Huilin Zhu, Wenxiang Song, Xiang Wu, Guilu Nanjing Xiaozhuang Univ Sch Elect & Engn Nanjing 211171 Peoples R China Jiangsu Key Construct Lab IoT Applicat Technol Wuxi Jiangsu Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Chongqing Univ Posts & Telecommun Key Lab Ind Internet Things & Networked Control Minist Educ Chongqing 400065 Peoples R China Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Jiangsu Peoples R China

This paper studies the energy efficiency optimization problem for coordinated multipoint (CoMP)-enabled and backhaul-constrained ultra-dense small-cell networks (UDNs). Energy efficiency is an eternal topic for future wireless communication networks;however, taking actual bottleneck of the backhaul link and the coordinated network architecture into consideration, it is difficult to find an effective way to improve the energy efficiency of the network. Aiming at this problem, we propose to combine cell association, subchannel allocation, backhaul resource allocation, and sleep/on of the cells together to develop an optimization algorithm for energy efficiency in UDN and then solve the formulated energy efficiency optimization problem by means of improved modified particle swarm optimization (IMPSO) and linear programming in mathematics. Simulation results indicate that nearly 13% energy cost saving and 21% energy efficiency improvement can be obtained by combining IMPSO with linear programming, and the backhaul link data rate can be improved by 30% as the number of small cells increases. From the results, it can be found that by combining IMPSO with linear programming, the proposed algorithm can improve the network energy efficiency effectively at the expense of limited complexity.

关键词： Linear programming

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CAE-RLSM: Consistent and Efficient Redundant Line Segment Merging for Online Feature Map Building

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2020年第7期69卷 4222-4237页

作者： Wen, Jian Zhang, Xuebo Gao, Haiming Yuan, Jing Fang, Yongchun Nankai Univ Inst Robot & Automat Informat Syst IRAIS Tianjin Key Lab Intelligent Robot TJKLIR Tianjin 300350 Peoples R China Chongqing Univ Posts & Telecommun Key Lab Ind IoT & Networked Control Minist Educ Chongqing 400065 Peoples R China

In order to obtain a compact line segment-based map representation for localization and planning of mobile robots, it is necessary to merge redundant line segments that physically represent the same part of the environment in different scans. In this article, a consistent and efficient redundant line segment merging (CAE-RLSM) approach is proposed for online feature map building. The proposed CAE-RLSM is composed of two newly proposed modules: one-to-many incremental line segment merging (OTM-ILSM) and multiprocessing global map adjustment (MP-GMA). Different from the state-of-the-art offline merging approaches, the proposed CAE-RLSM can achieve real-time mapping performance, which not only reduces the redundancy of incremental merging with high efficiency but also solves the problem of global map adjustment after loop closing to guarantee global consistency. Furthermore, a new correlation-based metric is proposed for the quality evaluation of line segment maps. This evaluation metric does not require manual measurement of the environmental metric information;instead, it makes full use of globally consistent laser scans obtained by simultaneous localization and mapping (SLAM) systems to compare the performance of different line segment-based mapping approaches in an objective and fair manner. Comparative experimental results with respect to a mean shift-based offline redundant line segment merging (MS-RLSM) approach and an offline version of one-to-one incremental line segment merging ((OTO)-T-2-ILSM) approach on both public data sets and self-recorded data set are presented to show the superior performance of CAE-RLSM in terms of efficiency and map quality in different scenarios.

关键词： Merging Measurement Lasers Buildings Mobile robots Redundancy Evaluation metrics map building mobile robots redundant line segment merging (RLSM)

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Semantic-based early warning system for equipment maintenance

Semantic-based early warning system for equipment maintenanc...

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2020 International Conference on Communications, Information System and Computer Engineering, CISCE 2020

作者： Geng, Daoqu Liu, Qilin Chongqing University of Posts and Telecommunications Ministry of Education Key Lab of Industrial Internet of Things and Networked Control Chongqing400065 China College of Automation Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781728197616

Equipment is the carrier to produce products, which plays an extremely important role in the industrial field and daily life. In the production process, to make the equipment run stably, it is necessary to maintain the equipment in time. At present, the equipment is developing, becoming more and more mechanized, automated and intelligent, and the requirements for equipment maintenance are also higher. In this paper, Semantic Web technology is introduced into the field of equipment maintenance, using Semantic annotation, rule-based reasoning and Semantic query to achieve equipment maintenance early warning. The experimental results show that the system can send out maintenance warning messages in time, and can meet the corresponding standards of equipment maintenance. © 2020 IEEE.

关键词： Semantic Web

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Platoon control of Connected Multi-Vehicle Systems Under V2X Communications: Design and Experiments

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2020年第5期21卷 1891-1902页

作者： Li, Yongfu Chen, Wenbo Peeta, Srinivas Wang, Yibing Chongqing Univ Posts & Telecommun Key Lab Intelligent Air Ground Cooperat Control U Chongqing 400065 Peoples R China Chongqing Univ Posts & Telecommun Key Lab Ind IoT & Networked Control Minist Educ Coll Automat Chongqing 400065 Peoples R China Georgia Inst Technol Sch Civil & Environm Engn Atlanta GA 30332 USA Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA Zhejiang Univ Coll Civil Engn & Architecture Hangzhou 310058 Peoples R China

This paper focuses on platoon control of multi-vehicle systems in a realistic vehicle-to-vehicle/vehicle-to-infrastructure (V2V/V2I, or V2X) communication environment. To this end, the communication probability of the beacon transmission is analyzed based on the carrier sense multiple access with collision avoidance (CSMA/CA) mechanism. Then, a new car-following model is proposed by considering the communication probability to capture the car-following behavior of connected vehicles (CVs) equipped with V2X communications. The stability of the proposed car-following model is analyzed using the perturbation method. In addition, a nonlinear consensus-based longitudinal control algorithm is designed by considering the interactions between CVs, and an artificial function-based lateral control algorithm is presented. The convergence of the longitudinal and lateral control algorithms is analyzed using the Hurwitz stable theorem and Lyapunov technique, respectively. Also, the string stability of the vehicular platoon is performed based on the infinity-norm method. Finally, field experiments are conducted using four CVs under the scenarios of platoon forming, vehicle merging, and vehicle diverging. The results verify the effectiveness of the proposed method in terms of the trajectory and velocity profiles.

关键词： Connected vehicle platoon control beacon transmission car-following model stability and consensus

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Deep Neural Network-Based Real-time Trajectory Planning for an Automatic Guided Vehicle with Obstacles

Deep Neural Network-Based Real-time Trajectory Planning for ...

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Chinese Automation Congress (CAC)

作者： Lai, Jialun Ren, Zhigang Wu, Zongze Liu, Yaqiang Xie, Shengli Guangdong Univ Technol Sch Automat Guangdong Key Lab IoT Informat Technol Guangzhou Peoples R China Chongqing Univ Posts & Telecommun Key Lab Ind Internet Things & Networked Control Minist Educ Chongqing Peoples R China Guangdong Univ Technol Sch Automat Guangdong HongKong Macao Joint Lab Smart Discrete Guangzhou Peoples R China

ISBN: (纸本)9781728176871

In this paper, a hybrid-intelligent real-time optimal control approach based on deep neural networks (DNNs) for an automatic guided vehicle (AGV) with obstacles is studied. The path planning problem of the AGV is formulated as an optimal control problem (OCP) and the numerical solution of the OCP can be obtained by discretizing the OCP into a nonlinear programming (NLP) problem. However, due to the change of the starting point and the high nonlinearity of the model, the solution process is usually difficult without good initial guesses. Multiple iterations are often needed and real-time performance cannot be easily achieved. To this end, we first use the Gauss pseudospectral method incorporated a smoothing technique to solve the AGV optimal control problem with high computational efficiency off-line. Subsequently, a DNNs is developed to learn the functional relationship between the optimal state and action pairs obtained by the approximate indirect method, and thus the resulting DNNs can generate the optimal control instructions in real time for the AGV navigation. Numerical results are illustrated to verify the real-time performance, control optimality and robustness of the developed DNN-based controller.

关键词： optimal control deep learning real-time trajectory planning control parameterization Gauss Pseudospectral Method

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