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检索条件"任意字段=International Symposium on Computer Networks and Distributed Systems"

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PROFINET Controller on Cloud

PROFINET Controller on Cloud

引用

international symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Hayri Mutlu Necdet Akyürek Ömer Korçak Dept. Research and Development Siemens A.S Istanbul Turkey Dept. Computer Engineering Marmara University Istanbul Turkey

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

PROFINET (Process Field Network) is an industrial Ethernet standard widely used for real-time data communication in automation systems, with over 60 million active nodes as of 2024. It facilitates fast and reliable cyclic data transmission, enabling real-time monitoring and control between devices such as programmable logic controllers (PLCs), sensors, and actuators. Traditionally, controllers and devices needed to operate within close physical proximity to ensure successful IO data exchange. However, advancements in network technology now allow PROFINET IO data to be transmitted over VPN connections with acceptable latency. This development enables real-time data to be redirected from factory-level devices to cloud systems, overcoming hardware limitations, enabling data storage and analysis, and supporting complex algorithms for more flexible and efficient production. This study investigates the feasibility and benefits of using a PROFINET controller deployed on a cloud virtual machine and communicating over VPN technology, with a focus on the efficiency and communication characteristics between the controller and its network.

关键词： Cloud computing Automation Protocols Real-time systems Virtual machines Virtual private networks Sensors Data communication Servers Standards

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Facility Location in 6G-aware Vehicular Edge Computing

Facility Location in 6G-aware Vehicular Edge Computing

引用

international symposium on Advanced networks and Telecommunication systems (ANTS)

作者： A Surayya Ch Madhu Bhushan Firoj Gazi Md. Muzakkir Hussain Department of Computer Science and Engineering SRM University AP Andhra Pradesh India

ISBN: (数字)9798350391725

ISBN: (纸本)9798350391732

This paper tackles the facility location problem in 6G -enabled Vehicular Edge Computing (VEC) systems, focusing on the optimal placement of Roadside Units (RSUs) and Unmanned Aerial Vehicles (UAVs). The goal is to minimize Quality of Service (QoS) degradation by addressing challenges like dynamic vehicle mobility, traffic variations, and real-time task offloading. A mathematical optimization model is proposed, considering latency, energy consumption, packet loss, and handover costs. To solve this complex problem, heuristic algorithms such as Hill Climbing, Tabu Search, Simulated Annealing, and A* search are introduced. Extensive simulations evaluate their performance on energy efficiency and cumulative latency across various traffic and network conditions. The results reveal the strengths of each algorithm, offering valuable insights for their application in VEC scenarios. These findings contribute to scalable, energy-efficient solutions for 6G-aware VEC networks, particularly in dynamic vehicular environments, advancing research in edge computing and network optimization.

关键词： 6G mobile communication Energy consumption Heuristic algorithms Quality of service Simulated annealing Search problems Energy efficiency Vehicle dynamics Optimization Edge computing

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Advancements in Suspicious and Violent Activity Recognition for Intelligent Video Surveillance

Advancements in Suspicious and Violent Activity Recognition ...

引用

Disruptive Technologies (ICDT), international Conference on

作者： Niyati Rana Deepak Parashar Nilesh Bahadure Hetal Jethani Sudipta Banerjee Kanhaiya Sharma Department of Computer Scinece & Engineering GSFC University Vadodara Gujarat Gujarat India Dept. of CSE Symbiosis Institute of Technology Pune Symbiosis International Univesity Pune Maharashtra India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

Recognition of suspicious or violent activity in video surveillance has become increasingly important in terms of public safety and security. This synthesis examined state-of-the-art methodologies for detecting anomalous human behaviors-such as machine learning, deep learning, and hybrid approaches. By analyzing key contributions across recent studies, we identify advancements in feature extraction, model architectures such as CNNs, LSTMs, and Conv3D, and their applications to datasets like UCF101 and custom video repositories. The comparative analysis shows promising aspects in terms of performance and reliability, with some techniques such as Time-distributed CNN getting accuracy improvements of over 90%. The issues of practical applications in a real-world scenario, problems with dealing with advanced datasets, and future research directions such as real-time implementation and ethical considerations were discussed. The present study provides an inclusive overview of the current trends in intelligent surveillance systems and the roadmap for innovations in the near future.

关键词： Deep learning Ethics Adaptation models computer architecture Streaming media Video surveillance Feature extraction Real-time systems Public security Convolutional neural networks

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Dermatological imaging of skin lesions in different skin phototypes using style transfer

Dermatological imaging of skin lesions in different skin pho...

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Annual IEEE symposium on computer-Based Medical systems

作者： Nohemí Sánchez-Medel Victor Romero-Bautista Raquel Díaz-Hernández Leopoldo Altamirano-Robles Biomedical Sciences and Technologies Instituto Nacional de Astrofisica Óptica y Electrónica Santa María Tonantzintla Puebla México Computer Sciences Instituto Nacional de Astrofisica Óptica y Electrónica Santa María Tonantzintla Puebla México

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

In dermatology, accurate identification and classification of skin lesions in various skin phototypes are essential for early and effective diagnosis. In this context, advances in artificial intelligence have highlighted the potential of Convolutional Neural networks as powerful tools for generating realistic medical images. This work aims to improve visual data availability to support computer-aided diagnosis. Beyond extending a dataset only with data augmentation techniques, we seek to enrich the quality and diversity of the data set including images generated for each proposed skin phototype. This study focuses specifically on the generation of dermatological images of skin lesions in six skin phototypes (Fitzpatrick scale), using the CNN model (VGG19) and applying Style Transfer. Once the images are generated, they are evaluated using two metrics: the structural similarity index and the Kullback-Leibler divergence. Seven hundred clinical images of seven common skin lesions were collected using the HAM10000 dataset, and 42 images were generated with the VGG19 model. The results suggest that applying the ST technique as a new approach to diversifying skin phototypes produces good results.

关键词： Measurement Visualization Accuracy Image synthesis Skin Lesions Convolutional neural networks

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A Mechanism for Controller Failover in distributed Software-Defined networks 8

A Mechanism for Controller Failover in Distributed Software-...

引用

8th international Conference on computer and Communication Engineering, ICCCE 2021

作者： Dharam, Poonam Dey, Mithila Saginaw Valley State University Department of Computer Science and Information Systems SaginawMI United States North Dakota State University Department of Computer Science Fargo United States

ISBN: (纸本)9781728110646

In Software Defined networks (SDN), reliability plays a major role in maintaining a consistent end-to-end connectivity and dealing with controller failures. A traditional SDN implementation relies on a central controller that runs the control plane. However, in a large-scale Wide Area Network (WAN) deployment, centralized approach has several limitations related to performance and scalability. To address these issues, distributed SDN where multiple controllers that work cooperatively to control a network are deployed. One key limitation of such a distributed network is failure of one or more controllers may cause severe issues like network outage and reduced Quality of Service (QoS). In this paper, we address the problem of controller failure in distributed SDN by proposing two controller failover techniques, namely (a) RandomWeightLoadBalancing and (b) ProgressiveAssignmentLoadBalancing. Our work focuses on load balancing the orphan switches, connected to a failed controller, among available controllers rather than overloading a single controller with all orphan switches. Simulation results show that our proposed solutions perform a successful reassignment of orphan switches and ensure that the load of each controller is well balanced. © 2021 IEEE.

关键词： Controllers

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Probing the Convergence of Vehicular Edge Metaverse and 6G: Blockchain-enabled Framework

Probing the Convergence of Vehicular Edge Metaverse and 6G: ...

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international symposium on Advanced networks and Telecommunication systems (ANTS)

作者： Shree Kumar Rajat Chaudhary Ishan Budhiraja School of Computer Science and Engineering Technology Bennett University Greater Noida India

ISBN: (数字)9798350391725

ISBN: (纸本)9798350391732

The convergence of vehicular networks and the Meta-verse, referred to as the Vehicular Edge Metaverse is set to revolutionize both transportation and in-car experiences. This paradigm shift envisions vehicles not only as modes of transport but also as immersive gateways to the Metaverse, offering passengers interactive and engaging experiences while on the move. The advent of 6G, with its ultra-fast speeds and minimal latency is crucial in enabling the real-time data synchronization and low-latency communication required for a seamless Vehicular Edge Metaverse experience. Additionally, blockchain technology can play a key role in ensuring secure and transparent data sharing and transactions within this ecosystem, fostering trust and enabling new business models. This paper explores the potential of this convergence, discussing the key enabling technologies such as 6G, edge computing, and blockchain, and their role in addressing the challenges of real-time synchronization, resource management, and security. Furthermore, we discuss the potential applications like augmented reality-enhanced driving assistance and immersive in-car entertainment, highlighting the transformative impact of the Vehicular Edge Metaverse on the future of transportation.

关键词： 6G mobile communication Metaverse Transportation Real-time systems Blockchains Security Resource management Synchronization Convergence Testing

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35th international symposium on distributed Computing, DISC 2021

35th International Symposium on Distributed Computing, DISC ...

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35th international symposium on distributed Computing, DISC 2021

ISBN: (纸本)9783959772105

The proceedings contain 61 papers. The topics discussed include: frugal byzantine computing;lower bounds for shared-memory leader election under bounded write contention;deterministic distributed algorithms and lower bounds in the hybrid model;ruling sets in random order and adversarial streams;impossibility of strongly-linearizable message-passing objects via simulation by single-writer registers;locally checkable labelings with small messages;randomized local fast rerouting for datacenter networks with almost optimal congestion;deterministic logarithmic completeness in the distributed sleeping model;space and time bounded multiversion garbage collection;and a tight local algorithm for the minimum dominating set problem in outerplanar graphs.

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Graphs, networks and Their Applications : Plenary Talk

Graphs, Networks and Their Applications : Plenary Talk

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international symposium on Computational Intelligence and Informatics

作者： József Solymosi Óbuda University Budapest Hungary

Graph theory is a beautiful part of mathematics. It has its own research line, understanding the structure of graphs under various constraints. Graphs can represent pairwise relations between objects. They are used to model complex systems from biology to machine learning. In this talk, I will explain some classical and new applications of graph theory. The specific areas of applications I will talk about are in•computer science•Biology•Social sciences•Linguistics•Business

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HetDAPAC: distributed Attribute-Based Private Access Control with Heterogeneous Attributes

HetDAPAC: Distributed Attribute-Based Private Access Control...

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IEEE international symposium on Information Theory

作者： Shreya Meel Sennur Ulukus Department of Electrical and Computer Engineering University of Maryland College Park MD

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

Verifying user attributes to provide fine-grained access control to databases is fundamental to an attribute-based authentication system. In such systems, either a single (central) authority verifies all attributes, or multiple independent authorities verify individual attributes distributedly to allow a user to access records stored on the servers. While a central setup is more communication cost efficient, it causes privacy breach of all user attributes to a central authority. Recently, Jafarpisheh et al. studied an information theoretic formulation of the distributed multi-authority setup with $N$ non-colluding authorities, $N$ attributes and $K$ possible values for each attribute, called an $(N, K)$ distributed attribute-based private access control (DAPAC) system, where each server learns only one attribute value that it verifies, and remains oblivious to the remaining $N-1$ attributes. We show that off-loading a subset of attributes to a central server for verification improves the achievable rate from $\fracdistributed{2K}$ in Jafarpisheh et al. to $\fracdistributed{K+1}$ in this paper, thus almost doubling the rate for relatively large $K$ , while sacrificing the privacy of a few possibly non-sensitive attributes.

关键词： Access control Costs Databases Authentication Privacy breach Servers Information theory

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Efficient Federated Learning Mechanism Based on Layer-wise Model Pruning

Efficient Federated Learning Mechanism Based on Layer-wise M...

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international symposium on Parallel and distributed Processing with Applications, ISPA

作者： Zhijie Jiang Zhe Zhang Yanchao Zhao College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

As a computing paradigm tailored for resource-constrained client devices, federated learning based on model pruning compresses the model size by removing unimportant parameters in the neural network, which has shown outstanding results in improving model efficiency and reducing computing costs. However, previous works simply customized a unified static model pruning rate, ignoring the heterogeneous capabilities of clients and the impact of pruning on different layers of the model during continuous iteration. In this paper, we design a novel Federated learning framework based on Dynamic Layer-wise Pruning, named FedDLP, which is capable of pruning at the hierarchical level depending on the client’s capability and model similarity to improve model efficiency and maintain model performance. This framework consists of two parts. First, pre-training customizes the initial pruning rate: We set the initial pruning rate for each layer according to the different capabilities of heterogeneous clients during the pre-training stage. Second, adaptively optimize the pruning rate: We use cosine similarity to quantify the contribution of each layer of the client model to the global model, thereby adaptively and dynamically optimizing the model pruning rate. Experimental results verify that our proposed method improves model efficiency by 2 to 3.5× compared to the state-of-the-art baselines, while achieving an accuracy difference of no more than 2% compared to the unpruned model.

关键词： Degradation Adaptation models distributed processing Accuracy Costs Federated learning Computational modeling Neural networks Tuning

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