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20th Chinese Intelligent systems conference

作者： Wang, Chunyong Guo, Dong Liaoning Univ Technol Sch Elect Engn Jinzhou 121001 Peoples R China

ISBN: (纸本)9789819786565;9789819786541;9789819786534

An adaptive backstepping control algorithm combined with RBF neural network is proposed for the control problem of electrohydraulic servo system caused by factors such as nonlinearity and parameter uncertainty. Firstly, the complex high-order nonlinear electrohydraulic servo system is decomposed into a low-order simple system with backstepping method. And the control law with unknown nonlinear function term is obtained. Secondly, the RBF neural network is applied to approximate the nonlinear function terms in the control law, and the adaptive rate is designed using the Lyapunov stability analysis method. Finally, simulation verification is conducted on the built Simulink simulation model, and the simulation results show that the adaptive control algorithm based on the RBF neural network backstepping method can achieve tracking control of the given signal and meet the desired dynamic performance criteria. In addition, in order to deal with the sensor noise problems that may be encountered in the actual deployment, the first-order filtering algorithm is introduced and verified in the simulation, which effectively reduces the noise interference.

关键词： Electro-hydraulic Servo systems Nonlinear control Backstepping control RBF Neural network Adaptive control

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Ivycide: Smart Intrusion Detection System Against E-IoT Driver Threats

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IEEE internet OF THINGS JOURNAL 2023年第10期10卷 8533-8546页

作者： Rondon, Luis Puche Babun, Leonardo Aris, Ahmet Akkaya, Kemal Uluagac, A. Selcuk Florida Int Univ Cyber Phys Syst Secur Lab Miami FL 33199 USA Florida Int Univ Adv Wireless & Secur Lab Miami FL 33199 USA

The rise of internet of Things (IoT) devices has led to the proliferation of smart environments worldwide. Although commodity IoT devices are employed by ordinary end users, complex environments, such as smart buildings, government, or private offices, or conference rooms require customized and highly reliable IoT solutions. Enterprise IoT (E-IoT) connect such environments to the internet and are professionally managed solutions usually offered by dedicated vendors As E-IoT systems require specialized training, closed-source software, and proprietary equipment to deploy. In effect, E-IoT systems present an unprecedented, under-researched, and unexplored threat vector for an attacker. In this work, we focus on E-IoT drivers, software modules used to integrate devices into E-IoT systems, as an attack mechanism. We first present PoisonIvy, a series of generalized proof-of-concept attacks used to demonstrate that an attacker can use a malicious driver to perform denial-of-service attacks, gain remote control, and abuse E-IoT system resources. To defend against E-IoT driver-based threats, we introduce Ivycide, a novel intrusion detection system used to detect unexpected E-IoT network traffic from an E-IoT system. Ivycide operates as a passive monitoring system within an E-IoT system using machine learning and signature-based classification to detect Poisonivy attacks. We evaluated the performance of Ivycide in a realistic E-IoT deployment. Our detailed evaluation results show that Ivycide achieves an average accuracy of 97% in classifying the type of Poisonivy attack and operates without modifications or operational overhead to the existing E-IoT systems.

关键词： internet of Things Smart buildings Monitoring control systems TV User interfaces Behavioral sciences Cyber attacks enterprise IoT (E-IoT) systems intrusion detection

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A Systematic Study and Detailed performance Assessment of SDN controllers Across a Wide Range of network Architectures 6th

A Systematic Study and Detailed Performance Assessment of SD...

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6th International conference on Soft Computing and Signal Processing, ICSCSP 2023

作者： Sujatha, V. Prabakeran, S. Department of Networking and Communication SRMIST Kattankulathur Chennai India

ISBN: (纸本)9789819984503

internet access is the primary motivating factor behind the revolutionary modern digital era. Almost everything is connected to the internet because of the internet of Things (IoT) concept. However, because typical IP networks have a close relationship between the data plane and the control plane, managing and configuring the network are extremely time-consuming and expensive to compute. Software-defined networking (SDN) has been recommended as a conceptual shift toward a perceived and functionally unified network control plane that will decrease the complexity of network administration. SDN makes it possible to program the network’s configuration and divides the data plane from the control plane. In the control plane, the controller supervises all data plane operations as its primary component. Therefore, for optimal performance, the controller’s performance and capabilities are crucial. The literature contains several controller designs for both broad and narrow networks have been proposed. Yet, there is just a little amount of thorough quantitative examination of them. In this article, a comprehensive qualitative comparison of various SDN controllers and a quantitative analysis of their performance in a variety of network scenarios are presented. We classify and categorize controllers, then compare them qualitatively. Several types of network controllers are compared and contrasted, including those used in IoT, blockchain, vehicle, and wireless sensor networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： controllers

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Optimal Decision-making System of Shield Tunneling Parameters Based on LSTM and MNSGA-ii

Optimal Decision-making System of Shield Tunneling Parameter...

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IEEE International conference on Automatic control and Intelligent systems (I2CACIS)

作者： Wang, Shuai Zhang, Yakun Gong, Guofang Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou Peoples R China

ISBN: (纸本)9798350372113;9798350372106

This paper presents an optimal decision-making method for shield tunneling parameters that integrates time series prediction and multi-mode intelligent multi-objective optimization. Firstly, we have developed a decision-making scheme for determining optimal tunneling parameters. To achieve this, we utilize a Long Short-term Memory network (LSTM) which learns from the extensive experience of shield drivers. Then, A comprehensive excavation performance evaluation index system considering TBM excavation specific speed and excavation specific energy has been proposed. Next, the Pareto front surfaces of each surrounding rock grade are obtained through Multi-mode discrete NSGA-ii (MNSGA-ii), and the final solution is selected based on the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) between the Pareto solution set and the LSTM predicted value. To evaluate the effectiveness of the proposed scheme, it is deployed in a shield machine using edge computer, then the engineering experiments were conducted. The performance of the proposed decision-making system is then tested and compared with that of the shield driver. The test results show that the proposed decision-making system can significantly improve the comprehensive tunneling performance. This demonstrates the feasibility and effectiveness of the proposed decision-making system.

关键词： Shield tunnel boring machine Decision-making system Time series prediction Multi-objective optimization Swarm intelligence

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Introspective Congestion control for Consistent High performance 25

Introspective Congestion Control for Consistent High Perform...

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20th European conference on Computer systems-EuroSys

作者： Jiang, Wanchun Li, Haoyang Wu, Jia Wang, Kai Ren, Fengyuan Wang, Jianxin Cent South Univ Changsha Peoples R China Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9798400711961

The congestion control (CC) algorithm is expected to achieve consistent high performance under different network environments. Traditionally, classic CCs are designed with the methodology of inferring path conditions to guide the rate adjustment. However, this methodology suffers from wrong path condition inferences in certain cases, which mislead the rate adjustment and lead to performance degradation. To avoid wrong path condition inferences, we develop the projection-based introspective method and design the introspective congestion control (ICC) algorithm in this paper. Specifically, the rate adjustment rules are designed to possess a specialized profile such that the projection of the profile can be distinguished under unchanged path conditions. In this way, the projection, which can be distinguished from the time series of delay signals in the frequency domain, facilitates ICC to extract more information for path condition inferences. Consequently, with the introspection on the projection, ICC can avoid being misled by wrong path condition inferences and thus achieve consistent high performance under different conditions. The advantages of ICC are confirmed through extensive experiments conducted on various locally emulated scenarios, global testbeds over the internet, and the Alipay platform.

关键词： Congestion control Consistent High performance Path Condition Inferences Introspective internet

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Artificial Neural network to Estimate Deterministic Indices in control Loop performance Monitoring 15th

Artificial Neural Network to Estimate Deterministic Indices ...

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15th International conference on Intelligent Human-Computer Interaction (IHCI)

作者： Gomez-Munera, John A. Diaz-Charris, Luis Jimenez-Cabas, Javier Corp Estudiantes & Profes Marinilla CORUM Marinilla Antioquia Colombia Univ Costa Barranquilla Atlantico Colombia

ISBN: (纸本)9783031538292;9783031538308

In many industrial processes, the control systems are the most critical components. Evaluate performance and robustness of a control loops is an important task to maintain the health of a control system and an efficiency in the process. In the area of control-Loop performance Monitoring (CPM), there are two groups of indices to evaluate the performance of the control loops: stochastic and deterministic. Using stochastic indices, a control engineer can calculate the performance indices of a control loop with the data in normal operation and a minimum knowledge of the process;but the problem is that to do a performance analysis is so hard, due it is necessary an advanced knowledge about the interpretation. Instead, an interpretation or analysis of deterministic indices is simpler;however, the problem with this approach is that an invasive monitoring of the plant is required to calculate the indices. In this paper, it is proposed to use an Artificial Neural network to estimate deterministic indices, considering as input the stochastic indices and some process information, taking advantage of the fact that data collection for stochastic indices is simpler.

关键词： Artificial Neural network control Loop performance Monitoring Deterministic Indices Stochastic Indices

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Who controls the Physical internet? A Review of Protocols and Algorithms 25th

Who Controls the Physical Internet? A Review of Protocols an...

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25th IFIP WG 5.5 Working conference on Virtual Enterprises (PRO-VE)

作者： Rebuglio, Massimo Ferrari, Andrea Zenezini, Giovanni Mangano, Giulio Ottaviani, Filippo Maria Politecn Torino Turin Italy

ISBN: (纸本)9783031717451;9783031717437;9783031717420

The Physical internet (PI) is a modern logistics pattern based on resources and information sharing, modeled after the Digital internet (DI). Running a PI network demands a participatory and distributed decision-making system, requiring communication protocols between nodes and optimization algorithms. Although different in nature, the Protocols and Algorithms (P&A) of the PI are often functionally equivalent to P&A of DI. This paper presents a systematic literature review on the control methods of a PI network. The results show that P&A can be "local", designed to operate in a distributed manner;"global", designed to centrally control the PI or parts of it;or for "orchestration", designed to centrally define operational parameters while avoiding direct control. This paper also draws considerations on the maturity state of PI's P&A, comparing them with those of the DI and with the process that led to their definition.

关键词： Physical internet Protocol Algorithms Supply Chain Logistics and supply chain management Digitalization Cyber-physical systems

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Resilient Robust Model Predictive control under Adaptive Event-Triggered Mechanism 6

Resilient Robust Model Predictive Control under Adaptive Eve...

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6th International conference on internet of Things, Automation and Artificial Intelligence, IoTAAI 2024

作者： Yu, Yanye Li, Huangju Wang, Jianhua Zhou, Min Zuo, Jiawei Huzhou University School of Engineering Huzhou China Huzhou Key Laboratory of Intelligent Sensing and Optimal Control of Industrial Systems Huzhou China

ISBN: (纸本)9798350386974

The problem of resilient robust model predictive control (RMPC) with hard constraints based on an adaptive event-triggered mechanism for a class of polytopic uncertain systems is investigated in this article. To reduce the burden of network communication, a novel adaptive event-triggering mechanism is introduced between the sensor and the controller (S/C) network. The objective of this paper is to design a resilient RMPC controller while considering the system performance degradation caused by the adaptive event-triggered mechanism, aiming to maintain high system performance while conserving communication resources. Moreover, by solving an online optimization problem, sufficient conditions are obtained to ensure that all states of the system are in the time-varying terminal constraint set. To conclusively validate the efficacy of the proposed resilient RMPC algorithm under the adaptive event-triggered mechanism, we adopt a specific distillation parameter example for illustration. © 2024 IEEE.

关键词： Predictive control systems

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Industrial internet Security Situation Assessment Method Based on Self-Attention Mechanism 3

Industrial Internet Security Situation Assessment Method Bas...

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3rd International conference on Artificial Intelligence, internet of Things and Cloud Computing Technology, AIoTC 2024

作者： Liu, Yitong Sun, Yan Liu, Caiyun Weng, Ying China Industrial Control Systems Cyber Emergency Reponse Team China

ISBN: (纸本)9798331530280

With the promotion of strategies such as 'internet plus', the deep integration of industrialization and informatization has accelerated, and industrial internet has become an important support for new economies such as intelligent manufacturing. However, there are numerous high-risk vulnerabilities in industrial control equipment and network systems, facing complex network security threats, leading to increasingly prominent security issues in industrial manufacturing environments. Therefore, industrial internet security situation assessment and prediction technology has become a research hotspot. This paper proposes an evaluation method based on self attention mechanism to address the issues of model construction and evaluation accuracy. By using self attention mechanism and LSTM neural network to analyze timeseries data, safety situation prediction is generated to improve evaluation accuracy. The experimental results show that the detection accuracy and F1 value of the algorithm proposed in this paper have better performance compared to traditional random forest algorithm, support vector machine, and K-nearest neighbor algorithm. © 2024 IEEE.

关键词： Smart manufacturing

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SEAL-CC: Scalable Latency Evaluation Methodology for internet-of-Things Services 24

SEAL-CC: Scalable Latency Evaluation Methodology for Interne...

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14th International conference on the internet of Things, IoT 2024

作者： Horvath, Kurt Klaus Kimovski, Dragi Spiess, Bernd Hohlfeld, Oliver Prodan, Radu ITEC University of Klagenfurt Klagenfurt Austria Distributed Systems group University of Kassel Kassel Germany

ISBN: (纸本)9798400712852

Traditional network measurement campaigns suffer from the lack of control over network infrastructure and the inability to evaluate communication performance directly, especially for the placement of highly distributed internet of Things (IoT) services. In response, we propose a novel Scalable Latency Evaluation Methodology for the Computing Continuum (SEAL-CC). SEAL-CC extends beyond short-term evaluations by capturing the long-term responsiveness of networks supporting IoT services on the computing continuum. It organizes and evaluates a network of nodes, offering insights for optimized IoT service placement in urban and international settings. Our contributions include a novel evaluation methodology tailored for IoT services over the computing continuum, a comprehensive framework for transparent network evaluation using distributed internet measurement platforms, and a real-life case-study validation with recommendations for IoT service placement. © 2024 Copyright held by the owner/author(s).

关键词： Velocity measurement

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