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检索条件"任意字段=Conference on Internet Performance and Control of Network Systems II"

共 4637 条记录，以下是21-30 订阅

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Goal-Oriented Transport Layer Protocols for Wireless control 20

Goal-Oriented Transport Layer Protocols for Wireless Control

引用

20th Annual IEEE International conference on Sensing, Communication, and networking (SECON)

作者： Kutsevol, Polina Ayan, Onur Pappas, Nikolaos Kellerer, Wolfgang Tech Univ Munich Chair Commun Networks Munich Germany Linkoping Univ Dept Comp & Informat Sci Linkoping Sweden

ISBN: (纸本)9798350300529

Goal-oriented communication is a promising approach to tailor the network resource management algorithms to the needs of particular applications, thus enhancing the efficiency of resource utilization and boosting the application performance. In the context of distributed cyber-physical systems and networked control systems, the design of a control-aware transport layer (TL) represents a realistic approach for goal-oriented communications since it can be integrated into generic control setups without making assumptions on particular hardware or network technologies and deliver enhanced end-to-end performance. This demo showcases the application performance of different TL schemes used for communication between the sensors and the controllers monitoring and actuating inverted pendulums, i.e., multi-dimensional plants. The nodes of the control loops are realized with Zolertia Re-Mote devices, and multiple control loops communicate over the shared wireless network using IEEE 802.15.4 standard. We use the demonstration testbed to compare the performance of conventional, state-of-the-art, and novel goal-oriented TL schemes by observing the emulated dynamics of inverted pendulums.

关键词： Inverted pendulum

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Intelligent Manufacturing Flexibility Scheduling Optimization Based on Hybrid NSGA-ii Algorithm 7

Intelligent Manufacturing Flexibility Scheduling Optimizatio...

引用

7th International conference on Mechatronics, Robotics and Automation

作者： Hu, Zhuoya Liu, Jun Xu, Ji Ye, Chaoqian Wuhan Inst Engn Sch Comp Sci & Engn Wuhan 430205 Peoples R China Key Lab Biomarkers & In Vitro Diag Translat Zheji Hangzhou 310063 Peoples R China Hubei Cent China Technol Dev Elect Power Co Ltd Hubei Engn Res Ctr Intelligent Digital Technol Ne Wuhan 430074 Peoples R China

ISBN: (纸本)9798350352481;9798350352474

The flexible job-shop problem is one of the classical problems that have attracted much attention in the field of industrial automation and control. For the Multi-Objective Flexible Job-shop Scheduling Problem (MOFJSP), this paper proposes a hybrid particle swarm Non-dominated Sorting Genetic Algorithm ii (NSGA-ii) to solve the problem. The high-quality solution of the problem is obtained through particle swarm optimization as part of the initial population of NSGA-ii, and an elite strategy is used to prevent the loss of outstanding individuals by mixing all the individuals of the parent and the offspring in a non-dominated sorting method. This approach not only facilitates automation in manufacturing and production but also enhances the control and optimization of complex systems. Furthermore, integrating intelligent transportation systems and the internet of Things (IoT) into the scheduling process ensures real-time fault diagnosis and fault-tolerant control, thereby improving the overall efficiency and reliability of the production system. The experimental results show that the hybrid optimization approach combining PSO and NSGA-ii exhibits superior performance in solving MOFJSP. This research contributes to the advancement of cyber-physical systems and the automation of complex industrial processes.

关键词： flexible job shop scheduling NSGA-ii PSO industrial automation control and optimization

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Explainable Reinforcement Learning for network Management via Surrogate Model 44

Explainable Reinforcement Learning for Network Management vi...

引用

44th IEEE International conference on Distributed Computing systems (ICDCS)

作者： Botta, Alessio Canonico, Roberto Navarro, Annalisa Univ Napoli Federico II DIET Dept Naples Italy

ISBN: (纸本)9798350354720;9798350354713

In recent years, the adoption of Machine Learning, particularly Reinforcement Learning (RL), for the control and management of communication networks has emerged. However, a critical challenge hindering its practical implementation is the lack of explainability inherent in these models, which prevents network administrators from adopting these techniques despite their great potential to improve network performance. This paper aims to enhance the trustworthiness of RL-based network management and control, by making the RL model explainable and providing administrators with transparent insights into the RL decision-making processes. With this aim, we propose a methodology that leverages surrogate models, specifically, Decision Trees (DTs), to create simplified yet interpretable representations of the original RL model, able to explain it. Experiments were conducted to evaluate the efficacy of our method, demonstrating that the surrogate model achieves about 94% accuracy in imitating the original RL model. Additionally, the surrogate model significantly improves the explainability of the entire system by automatically generating graphical representations, in the form of DTs for interpreting the RL decisions.

关键词： Explainability network Management Reinforcement Learning SD-WAN

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Industrial internet of Things Intrusion Detection Model Integrating Graph Attention network and Gated Temporal Convolutional network 7

Industrial Internet of Things Intrusion Detection Model Inte...

引用

7th International conference on Advanced Algorithms and control Engineering, ICAACE 2024

作者： Peng, Chenghe Zhang, Ying College Of Information Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9798350361445

In recent years, the application of the Industrial internet of Things (iioT) in industry has become increasingly important. However, because iioT devices and systems are connected to the internet, they may face the risk of malicious intrusions that can cause serious damage to production processes and data security. Intrusion detection systems (IDS) can be used to monitor iioT for malicious activities and develop response strategies. Therefore, this article proposes an intrusion detection model called GTRGAT to ensure the network security of iioT. In particular, the GTRGAT model uses GTCN to quickly pull out sequence features from iioT traffic. GTCN combines convolutional operations and gating mechanisms, aiming to process time series data more efficiently and capture its intrinsic patterns. By using the TON-IoT dataset, the performance of the GTRGAT model is verified, showing that it can accurately detect intrusions. The experiment also showed that the GTRGAT model works better than other advanced methods, so it can be used as a workable way to find intrusions in industrial IoT networks. © 2024 IEEE.

关键词： internet of things

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network Traffic Prediction and Congestion control Using a Feed Forward Neural network 12

Network Traffic Prediction and Congestion Control Using a Fe...

引用

12th IEEE International conference on Intelligent systems, IS 2024

作者： Nwigwe, JohnPaul Martin, Iain Ramsay, Craig University of Dundee United Kingdom

ISBN: (纸本)9798350350982

The surge in internet of Things (IoT) usage has precipitated the need to replace classical internet network prediction and congestion control methods with a more efficient and reliable learning-based approach. Many machine-learning based approaches have been offered by different studies to solve this problem but not without limitations. In this study, we propose a new feed forward neural network with a multi-channel routing congestion control system (FFNN-MCRCCS) to optimize network prediction and congestion control problem. The nodes in the proposed network are mutually connected to enable the firing of neurons in a more decentralized manner to update their weights in order to call the recursive square function to predict the traffic. The exponent value of the recursive function serves as a parameter to determine the channel with the minimum congestion threshold for packet transmission. The results of the experiment show that the proposed model has the capability to optimize network traffic for effective utilization of network resources more than the baseline and the counterpart methods. The performance evaluation metrics used for the experiment include mean square error throughput, link utilization, average jitter, settling time, queue length and network and network convergence. © 2024 IEEE.

关键词： Congestion control (communication)

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Tamperproof Data Transmission to Offline IoT Devices in a Zero-Trust Environment

Tamperproof Data Transmission to Offline IoT Devices in a Ze...

引用

International conference on Computing, networking and Communications (ICNC)

作者： Vogel, Richard Manthey, Robert Baumgart, Matthias Roschke, Christian Ritter, Marc Vodel, Matthias Hsch Mittweida Fac Appl Comp Sci & Biosci D-09648 Mittweida Germany

ISBN: (纸本)9798350371000;9798350370997

This paper presents a holistic approach for transmitting arbitrary data to local internet-of-Things (IoT) devices using only public services in a zero-trust environment. The approach features a variety of benefits, namely (i) eliminates the need for service providers to deploy their own costly infrastructure, (ii) enables the receiving device to operate without an active network connection, (iii) ensures that the data can be proven untampered on the IoT device itself, (iv) verifies both the validity and recency of the information, (v) requires low administrative and technical efforts, (vi) allows for wireless data updates, including the timeliness of current information, by any participant due to the zero-trust assumption. The described methodology utilizes distinct features of Proof-of-Work (PoW)-based programmable blockchain systems. This work will focus on the usage of Ethereum Classic (ETC) as base layer for trust, the validity and recency of the information. The proposed approach has wide-ranging practical applications, including programmable, rule-based locking systems such as smart locks used in corporate and institutional buildings, cars, and hotels. It also facilitates other forms of access control, such as ticket systems, health certificates, and proof-of-possession for resources or achievements. Due to the zero-trust assumption, data updates as well their recency can be updated by any participant of the system.

关键词： internet of Things Security Blockchain Access control Wireless Communication Distributed systems

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A Way to Implement network Services in a Data Center

A Way to Implement Network Services in a Data Center

引用

2024 Wave Electronics and its Application in Information and Telecommunication systems, WECONF 2024

作者： Buzhin, I.G. Antonova, V.M. Gnezdilov, V.S. Mironov, Yu.B. Gayfutdinov, E.A. Moscow Technical University Of Communications And Informatics Moscow Russia

ISBN: (纸本)9798350364989

In recent years, IP-fabric has often been used in data center networks, which is a set of network equipment (usually switches) interacting via control protocols, which provides unified addressing, security, etc. services, as well as data delivery along the optimal route. With such an organization, the implementation of some services is transferred to the virtualization of network functions. This article suggests an effective way to implement virtualization of network functions and deliver traffic to it in the IP fabric of a data center. The method is based on VPP (Vector Packet Processing platform) and FRR (Free Range Routing), VxLAN (Virtual extensible local area network), EVPN (Ethernet VPN) and ICMP (internet control Message Protocol) technologies. The results of test measurements of the processing of various traffic on the data plane are shown. The results of experimental tests show that on Xeon Cascade Lake core, VPP technology produces a performance of about 20 Mpps with IPv4 traffic. Combinations of IPv4 lookup, VxLAN, Encap/Decap, and ACL (Access control List) lookup processing show lower performance. © 2024 IEEE.

关键词： internet protocols

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Decentralized control of UAV Swarms for Bandwidth-aware Video Surveillance using NMPC

Decentralized Control of UAV Swarms for Bandwidth-aware Vide...

引用

International conference on Unmanned Aircraft systems (ICUAS)

作者： Rezaei, Mohammad Amin Manfredi, Gioacchino Racanelli, Vito Andrea De Cicco, Luca Mascolo, Saverio Politecn Bari Dipartimento Ingn Elettr & Informaz Via Orabona 4 I-70125 Bari Italy

ISBN: (纸本)9798350357899;9798350357882

This paper proposes a framework for controlling a drone swarm to achieve two goals: i) covering a desired region of interest through onboard cameras that capture videos to be sent in real-time to a Ground control Station (GCS), and ii) ensuring the highest video quality possible given the available internet network bandwidth. Indeed, the quality of received videos depends on both the available bandwidth, which directly influences video encoding bitrate, and the altitude of drones, which influences pixel density. Thus, contrary to the conventional assumption of uniform drone altitudes, we let drones to track a reference altitude that is function of the time-varying available bandwidth to improve visual quality. To achieve the aforementioned goals, we propose a leader-follower multi-agent system formation control problem. In this setup, the leader tracks a desired path using Nonlinear Model Predictive control (NMPC) to cover the area of interest. Follower agents track the leader using NMPC, aiming at maximizing both the total coverage area and the quality of the videos sent to the GCS, considering the constraints imposed by the network available bandwidth. At the same time, we formulate the NMPC problem to ensure that the swarm maintains a formation characterized by a given overlap percentage between the videos captured by the drones while avoiding collisions. This allows dynamical stitching of the received videos at the GCS, enabling the execution of computer vision algorithms for tasks such as object detection and surveillance.

关键词： Unmanned Aerial Vehicle (UAV) Multi-agent systems Formation control Non-linear Model Predictive control (NMPC) Communication-aware control

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Resource Allocation of Large-Scale Communication network based on Machine Learning 2

Resource Allocation of Large-Scale Communication Network bas...

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2nd IEEE International conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Zhang, Zhuxin Mo, Ruifeng Hou, Xiaoqi Wei, Xin Guo, Suzhen Research Institute North Automatic Control Technology Taiyuan China

ISBN: (纸本)9798350317558

With the continuous development of mobile internet technology, its demand for network performance is also increasing. Although the traditional multi-level structure of network resources enhances the scalability and independence of the network, it cannot be used effectively, nor can it intelligently configure network resources. To this end, this paper explores a new network resource allocation method, namely, a machine learning-based large-scale communication network resource allocation method. This paper first explains the concepts of communication network resource allocation and machine learning, and then proposes the principle of communication network resource allocation based on machine learning. Finally, through experiments, this paper analyzes that the bandwidth utilization rate, data delay and packet loss rate of the communication network resource allocation based on the method in this paper are 78%, 5ms and 0.05%, respectively, and the comprehensive performance is better than other communication network resource allocation methods. © 2024 IEEE.

关键词： Communication network Resource Allocation Information Age Machine Learning Optimization Capability

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D-PSO: An Optimization Algorithm for Wireless Sensor network Layout in Power systems 9

D-PSO: An Optimization Algorithm for Wireless Sensor Network...

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9th International conference on Automation, control and Robotics Engineering (CACRE)

作者： Ma, Pengwei Zhu, Yuanjiao Sun, Zheng Wei, Jingyi Luo, Yunchen Zhou, Jie Shihezi Univ Coll Informat Sci & Technol Shihezi Peoples R China

ISBN: (纸本)9798350350319;9798350350302

The effective deployment of wireless sensor networks (WSNs) is a crucial foundation for the intelligent development of power systems. To address the optimization of wireless sensor distribution in power systems, this paper proposes a novel method named the Distributed Particle Swarm Optimization algorithm (D-PSO). This method mitigates the premature convergence issue of heuristic algorithms by introducing a regional operator. Additionally, considering the high-interference environment in power systems, relay node strategy (RNS) is incorporated to ensure communication quality. Simulation results validate the effectiveness and superiority of the D-PSO method and demonstrate the necessity of the RNS. Compared to some advanced particle swarm algorithms, this method better balances energy consumption, coverage, and communication quality, thereby significantly enhancing the overall performance of the wireless sensor network.

关键词： wireless sensor network power systems Particle Swarm Optimization algorithm

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