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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Wu, Ruixuan Shi, Yuliang Yuan, Haitao Bi, Jing Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9798350337020

Mobile devices (MDs) cannot fully run all computation/delay-sensitive tasks due to their limited computing resources. Mobile edge computing (MEC) meets the demand by providing massive resources for MDs and offloading task partitions to MEC servers. However, task offloading also brings communication delay and energy consumption. Therefore, it is challenging to associate resource-constrained MDs with appropriate MEC servers to minimize power consumption. To address this problem, a constrained mixed integer nonlinear program is formulated to optimize the total energy consumption of the system including MDs and MEC servers. To solve this problem, this work designs an improved meta-heuristic optimization algorithm called Self-adaptive and Multi-population Differential Annealed Optimization (SMDAO). Experimental results demonstrate that compared with its two state-of-the-art peers, the proposed SMDAO yields the best solution with the smallest total energy consumption in the least time. © 2023 IEEE.

关键词： computation offloading energy optimization Mobile edge computing multi-population optimization simulated annealing

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Energy Cost and Performance-Sensitive Bi-objective Scheduling of Tasks in Clouds

Energy Cost and Performance-Sensitive Bi-objective Schedulin...

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2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020

作者： Yuan, Haitao Bi, Jing Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Faculty of Information Technology Beijing University of Technology Beijing100124 China New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781728168531

Cloud computing attracts a growing number of organizations to deploy their applications in distributed data centers for low latency and cost-effectiveness. The growth of arriving instructions makes it challenging to minimize their energy cost and improve Quality of Service (QoS) of applications by optimizing resource provisioning and instruction scheduling. This work formulates a bi-objective constrained optimization problem, and solves it with a Simulated-annealing-based Adaptive Differential Evolution (SADE) algorithm to jointly minimize both energy cost and instruction response time. The minimal Manhattan distance method is adopted to obtain a knee for good tradeoff between energy cost minimization and QoS maximization. Real-life data-based experiments demonstrate SADE achieves lower instruction response time, and smaller energy cost than several state-of-the-art peers. © 2020 IEEE.

关键词： Simulated annealing

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Latency-Minimized Computation Offloading in Vehicle Fog Computing with Improved Whale Optimization Algorithm

Latency-Minimized Computation Offloading in Vehicle Fog Comp...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bi, Jing Xue, Xiangdong Yuan, Haitao Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science Lyle School of Engineering DallasTX United States

ISBN: (纸本)9798350337020

Fog computing provides lower latency and higher bandwidth compared to cloud computing and is widely used in Internet of Vehicles (IoV). Vehicles cannot compute all tasks locally due to their limited computing power and battery capacity. Thus, it is a useful way to offload some tasks of vehicles to other resource-rich servers. However, due to the high mobility of vehicles, there may be a failure of returning computing results. Thus, it is a challenge to minimize the latency of tasks while meeting the constraint of energy consumption. This work proposes a vehicle-fog offloading system that offloads tasks to fog servers or idle vehicles which is a probabilistic offloading problem. So this work proposes an improved optimization algorithm called an adaptive Lévy flight-based Whale optimization algorithm with Hierarchical learning (LWH) to solve this problem. Simulation experiments show that LWH has strong global search capability and outperforms its five typical and widely used algorithms. © 2023 IEEE.

关键词： computation offloading fog computing Lévy flight Vehicular networks whale optimization algorithm

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Can adaptive strategies sustain bidirectional LoRaWAN traffic?

Can adaptive strategies sustain bidirectional LoRaWAN traffi...

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Workshop on Metrology for Industry 4.0 and IoT

作者： Emiliano Sisinni Alessandro Depari Paolo Bellagente Alessandra Flammini Ivanovitvh Silva Thommas Flores Paolo Ferrari Dept. of Information Engineering University of Brescia Brescia ITALY Dept. of Computer Engineering and Automation UFRN Natal BRAZIL Postgraduate Program in Electrical and Computer Enigeneering UFRN Natal BRAZIL

Low Power Wide Area Networks (LPWANs) are a viable solution for addressing the requirements of Internet of Things (IoT) applications that can tolerate sporadic updates, possibly only in the uplink (from the field towards the cloud and the user) direction. LoRaWAN is currently the most diffused example of LPWAN, exploiting LoRa radios. LoRa, an enhanced version of chirp spread spectrum modulation, trades off the radio sensitivity for the data rate, permitting extensive area coverage. However, the price is a relatively long frame duration, leading to high collision probability in dense, asynchronous scenarios; fortunately, polarity inversion minimizes collisions between uplink and downlink traffic. Therefore, adaptive strategies (based on some feedback from the backend) have also been suggested to adapt the data rate depending on the environment condition dynamically. This work compares the ADR (Adaptive Data Rate) and the ADP (Adaptive Data Payload) strategies when bidirectional traffic exists, using a purposely designed simulator. Results considering a different number of gateways show that ADP tries to maximize the amount of data effectively received in both direction but suffer from the adoption of longer frame duration, leading to higher collision probability. In contrast, ADR tries to force the adoption of the fastest data rate, limiting the overall amount of transferred data.

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Network Anomaly Detection with Stacked Sparse Shrink Autoencoders and Improved XGBoost

Network Anomaly Detection with Stacked Sparse Shrink Autoenc...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bi, Jing Guan, Ziyue Yuan, Haitao Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science Lyle School of Engineering DallasTX United States

ISBN: (纸本)9798350337020

Efficient and accurate identification of network anomalies is of great significance to the construction of network security systems in the information age. It is highly challenging to accurately detect abnormal behaviors in the increasing network data. Currently, classification methods based on feature extraction of autoencoders have been proven to be suitable for network anomaly detection. However, traditional detection models with autoencoders have poor detection accuracy in the face of massive network features. In addition, the hyperparameter optimization of their models cannot be effectively solved. For network anomaly detection, this work proposes a new network anomaly detection method named SAXP, which integrates Stacked sparse shrink Autoencoders and a XGBoost model based on genetic simulated annealing Particle swarm optimization (GSPSO). Specifically, features extracted by stacked sparse shrink autoencoders are introduced into the XG Boost model for classification, and GSPSO is used to optimize the hyperparameters of XGBoost. Experimental results based on two real-life data sets demonstrate that the proposed SAXP achieves higher recognition accuracy than several state-of-the-art algorithms. © 2023 IEEE.

关键词： autoencoders feature extraction Network anomaly detection particle swarm optimization XGBoost

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Web Traffic Anomaly Detection Using a Hybrid Spatio-temporal Neural Network

Web Traffic Anomaly Detection Using a Hybrid Spatio-temporal...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bi, Jing Xu, Lifeng Yuan, Haitao Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China School of Engineering Dept. of Computer Science in Lyle Southern Methodist University DallasTX United States

ISBN: (纸本)9798350337020

Nowadays, rapid development of Internet has brought a sharp increase in traffic data. Abnormal traffic haS serious impact on network security. Traffic anomaly detection can be achieved by extracting characteristics of network traffic to detect anomalous intrusions, and therefore, anomaly detection algorithms are of great significance to maintenance of network security. This work proposes a hybrid spatio-temporal neural network with attention named CTGA to effectively identify anomalous traffic. CTGA combines a Convolutional neural network (CNN), a Temporal convolutional network (TCN), a bidirectional Gated recurrent unit network (BiGRU), and a self-Attention mechanism. It automatically extracts temporal and spatial features of sequences from raw data by sliding window preprocessing followed by CNN, TCN, BiGRU, and the self-attention mechanism to detect anomalous data. CNN is used to extract spatial features of time sequences and reduce the loss of spatial information. In the sequence, TCN obtains short-term features. Long-term dependencies in the data are captured by BiGRU, and the self-attention mechanism obtains important information in the sequence. Finally, experiments with the real-life Yahoo S5 dataset prove that CTGA outperforms other approaches substantially. © 2023 IEEE.

关键词： Anomaly detection bidirectional gated recurrent unit convolutional neural network self-attention temporal convolutional network

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Fuzzy automata for fault diagnosis: A syntactic analysis approach

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3rd Hellenic Conference on Artificial Intelligence, SETN 2004

作者： Rigatos, Gerasimos G. Tzafestas, Spyros G Industrial Systems Institute University Campus of Patras Building A ’ Rion Patras26500 Greece National Technical University of Athens Dept. of Electrical and Computer Engineering Intelligent Robotics and Automation Lab Zografou Campus Athens15773 Greece

ISBN: (纸本)3540219374

Fuzzy automata are proposed for fault diagnosis. The output of the monitored system is partitioned into linear segments which are assigned to pattern classes (templates) with the use of fuzzy membership functions. A sequence of templates is generated and becomes input to fuzzy automata which have transitions that correspond to the templates of the properly functioning system. If the automata reach their final states, i.e. the input sequence is accepted by the automata with a membership degree that exceeds a certain threshold, then normal operation is deduced, otherwise, a failure is diagnosed. Fault diagnosis of a DC motor and detection of abnormalities in the ECG signal are used as case studies. © Springer-Verlag Berlin Heidelberg 2004.

关键词： DC motors

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Improved image coding algorithm based on embedded zerotree

Improved image coding algorithm based on embedded zerotree

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SNPD 2007: 8th ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing

作者： Xuhong, Liu Fuheng, Liu Guijuan, Kuang Xiu, Yi Dept. of Computer and Automation Beijing Institute of Machinery Beijing 100089 China College of Information Science and Engineering Laiyang Agriculture University Qingdao 266109 China Shandong Cadre School of Quality Technology and Supervision Jinan 250014 China

ISBN: (纸本)0769529097

This paper presents an improved embedded zerotree wavelet (EZW) coding algorithm. According to the characteristic of coefficients and human visual system (HVS), an attempt is made to improve Shapiro's EZW algorithm. The improved algorithm pays more attention to the edge of one image because human visual system is sensitive to the distortion of image edge information. Experiments results show that the improved algorithm performs better than EZW in reconstruction image quality, especially in the case of low rate. © 2007 IEEE.

关键词： Image coding

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Characterization of Singular Controls for Nonholonomic Path Planning

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IFAC Proceedings Volumes 1996年第1期29卷 2460-2465页

作者： Dan O. Popa John T. Wen Center for Advanced Technology in Automation Robotics and Manufacturing Dept. of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180

A class of Iterative algorithms have been proposed in recent years for the nonholonomic motion planning problem. The convergence of these algorithms predicates on the control signal in each iteration be "nonsingular". At the present, the singularity structure is only identified for the unicycle and front-wheel-drive car kinematic models. In this paper, we extend the consideration to all systems reducible to one-chain form, which include unicycle, car, as well as any N-trailer system. In particular, we show that a control is singular if and only if the first control variable is identically zero. We also identified all singular controls for the ball rolling on a plate problem. which is not reducible to the one-chain form.

关键词： Nonholonomic motion planning Nonholonomic Systems Path Planning Gradient algorithms Singular Controls

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A unified angle control scheme for hypersonic vehicle based on disturbance rejection 21

A unified angle control scheme for hypersonic vehicle based ...

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21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017

作者： Piao, Minnan Zhu, Kai Sun, Mingwei Chen, Zengqiang Dept. of Automation and Intelligent Science College of Computer and Control Engineering Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Beijing Aerospace Technology Institute Beijing100074 China

ISBN: (数字)9781624104633

ISBN: (纸本)9781624104633

Hypersonic vehicles are characterized with strong nonlinearities, coupling effects and uncertainties as well as fast time-varying parameters, which impose great difficulty to the attitude control. This study proposes a unified scheme for all the Euler angles, angle of attack, and sideslip angle. First, three controllers based on active disturbance rejection control (ADRC) are designed for the Euler angles respectively, in which the external disturbances and the internal uncertainties can be estimated by the extended state observer (ESO) and compensated in real time actively. Then the geometric relations among the angles with different time scales are utilized to transform the commands of α and β into the commands of the pitch angle and the yaw angle. Next the stability-margin tester method is employed to tune the controller parameters, which guarantees the stability and robustness of the control system. 1000 nonlinear six-degree-of-freedom Monte Carlo simulation results demonstrate the good tracking performance and the robustness of the proposed control method. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hypersonic vehicles

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