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检索条件"任意字段=6th International Conference on Distributed Computing and Internet Technology"

共 8755 条记录，以下是11-20 订阅

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A fog and blockchain-based distributed Virtual Private Networks (VPN) 20

A fog and blockchain-based distributed Virtual Private Netwo...

引用

20th Annual international conference on distributed computing in Smart Sensor Systems and the internet of things (DCOSS-IoT)

作者： Trabelsi, Rahma Fersi, Ghofrane Jmaiel, Mohamed Natl Sch Engineers Sfax ReDCAD Lab Sfax Tunisia

ISBN: (纸本)9798350369458;9798350369441

the internet of things (IoT) is a breakthrough technology that interconnects and empowers numerous smart devices allowing them to communicate, collect, and exchange data. the most challenging issue in IoT networks is securing exchanged data. Virtual Private Networks (VPNs) have a significant impact on ensuring security within IoT systems. So implementing a VPN-based solution can bring multiple security values to IoT systems, especially for exchanged data. However, most VPN-based solutions rely on a single central server responsible for managing all VPN connections. this presents a major problem when the number of managed VPNs increases because it will lead to the performance deterioration of the VPN server and can even lead to a single point of failure problem. We propose in this paper a distributed VPN-based solution that relies on distributed fog nodes playing the role of VPN servers. To determine the VPN server responsible for a specific communication, a fully decentralized and efficient search is guaranteed within the fog nodes through the utilization of the DHT-based Chord protocol. To enforce security and immutability, blockchain is used to verify the different criteria of a new requester to join a specific VPN. the performance evaluations have shown that our solution is efficient in terms of cost, time, and complexity.

关键词： IoT Security Blockchain distributed Virtual Private Network Fog computing

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Adaptive Dynamic Adversarial Training with Real-Time Feedback in 6G 20

Adaptive Dynamic Adversarial Training with Real-Time Feedbac...

引用

20th Annual international conference on distributed computing in Smart Sensor Systems and the internet of things (DCOSS-IoT)

作者： Iakami, Ahmed I. Pissinou, Niki Rajhi, Mohammed Florida Int Univ Sch Comp & Informat Sci Miami FL 33199 USA Jazan Univ Fac Comp Sci & Informat Technol Jazan Saudi Arabia

ISBN: (纸本)9798350369458;9798350369441

the emergence of 6G communications brings forth both unprecedented opportunities and security challenges. this work introduces a novel method, dynamic adversarial training incorporating real-time feedback (DAT-RTF), to bolster the resilience of machine learning models in 6G mmWave beamforming prediction against adversarial attacks. By enabling models to adapt to new threats, DAT-RTF maintains their robustness. this dynamic approach, leveraging continuous feedback from the network, adjusts and refines defense mechanisms to remain effective against a range of adversarial strategies. We tackle the issues of resource demand and overfitting, offering strategies to enhance performance without sacrificing security. Our method represents a significant advancement in protecting 6G networks from evolving adversarial threats.

关键词： 6G communications machine learning adversarial training real-time feedback mmWave beamforming network security

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IoTinuum: the IoT computing Continuum 20

IoTinuum: The IoT Computing Continuum

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20th Annual international conference on distributed computing in Smart Sensor Systems and the internet of things (DCOSS-IoT)

作者： Kamienski, Carlos Zyrianoff, Ivan Bittencourt, Luiz Fernando Di Felice, Marco Fed Univ ABC Santo Andre SP Brazil Univ Bologna Bologna Italy Univ Estadual Campinas Campinas SP Brazil

ISBN: (纸本)9798350369458;9798350369441

IoT smart applications must deal with the inherently distributed nature of IoT infrastructures that may vary among different deployments. For example, in urban environments, some deployments may require distributed edge nodes to support the sensors and actuators, while others may skip this processing stage and go directly to the cloud. We propose the concept of an IoT computing Continuum, or IoTinuum, with multiple computing stages spread over the distributed IoT infrastructure. We present the modeling and implementation of two urban use cases for a 6-stage IoTinuum: smart drone delivery and smart structural monitoring. In our experience, the IoTinuum improves the understanding of function placement in application development and reveals important performance tradeoffs.

关键词： edge computing fog computing IoT smart applications

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Overview of Vehicle Edge computing and Its Security 6th

Overview of Vehicle Edge Computing and Its Security

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6th international conference on Security and Privacy in New computing Environments, SPNCE 2023

作者： Han, Shaodong Wang, Maojie Chen, Guihong Guangdong Polytechnic Normal University Guangzhou510635 China

ISBN: (纸本)9783031736988

the internet of Vehicles (IoV) is a part of the internet of things (IoT). With the continuous development of the internet of things technology, the internet of Vehicles technology has also made great progress. However, as more and more vehicles are connected to the internet of Vehicles, the calculation and transmission of data in the internet of Vehicles becomes more and more difficult, and at the same time, it is inevitable to face the pressure of data security and privacy protection. In order to solve the above problems, academia and industry have adopted many methods, combining mobile edge computing technology with the internet of Vehicles to establish a vehicle edge computing network to solve the problems of data computing and transmission. Introducing blockchain technology and federated learning technology into vehicle edge computing. therefore, the network addresses the issues of data security and privacy protection. Based on these, this paper summarizes the research results of many scholars in related fields, in order to provide reference and reference for subsequent related research. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Federated learning

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Event-Triggered Switched Observers for Networked distributed Multi-Agent Systems via Cloud computing 6

Event-Triggered Switched Observers for Networked Distributed...

引用

6th international conference on Electronic Engineering and Informatics, EEI 2024

作者： Zhang, Chen Ren, Hongru Ma, Hui Zhou, Qi School of Automation Guangdong University of Technology Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China School of Mathematics and Statistics Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9798350353594

this paper designs event-triggered switched observers for the networked distributed multi-agent systems based on the cloud computing systems. Firstly, a novel cloud computing system architecture is designed, in which each group of agents can interact with each others through distributed cloud nodes, and each cloud node also serves as an event-triggered switched observer to observe the topologies of the systems. Secondly, event-triggered switched observers are designed, which can assist distributed agents in accurately obtaining information from the leader, even with continuous switching topologies. then, through stability analysis, we demonstrate the effectiveness of the observers. Finally, we prove the feasibility of the observers through simulation. © 2024 IEEE.

关键词： distributed cloud

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(POSTER) Enhancing Structural Health Monitoring with On-device AI 20

(POSTER) Enhancing Structural Health Monitoring with On-devi...

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20th Annual international conference on distributed computing in Smart Sensor Systems and the internet of things (DCOSS-IoT)

作者： Lee, Junhak Hwang, Chungwhan Park, Jaehyun Park, Tae Rim Inha Univ Dept Info & Comm Engn Incheon South Korea Inha Univ Dept Elect & Comp Engn Incheon South Korea Ino On Inc Seoul South Korea

ISBN: (纸本)9798350369458;9798350369441

this paper presents a service model for structural health monitoring (SHM) by leveraging on-device AI techniques. Unlike conventional SHM systems relying on server-based diagnostics, our approach incorporates recent advancements in lightweight AI platforms to enable real-time diagnostics directly on the sensor nodes. this integration enhances both real-time performance and accuracy while significantly reducing network load by minimizing the need for data transfer to centralized servers. through the experimentation using real data collected from a pedestrian bridge, we demonstrate the feasibility and efficacy of the on-device AI approach for SHM. By seamlessly integrating on-device AI into IoT infrastructure, our approach not only offers improved real-time performance and accuracy but also showcases the potential of AI in optimizing SHM systems.

关键词： Structure health monitoring internet of things (IoT) on-device AI wireless sensor network

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A Systematic Approach for Performance Efficiency of distributed Networks using Machine Learning Techniques and Network Simulator 2 6

A Systematic Approach for Performance Efficiency of Distribu...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Parveen Akhther, A. Veera Subrahmanyam, N. Charan Sai, A. Prasanth, V.S. Dept. of CSE Sathyabama Institute of Science & Technology Chennai India Dept. of ECE Madanapalle Institute of Technology & Science Andhra Pradesh India

ISBN: (纸本)9798331522667

In the rapidly evolving domain of distributed networks, including cloud computing and edge systems, achieving optimal performance efficiency is critical. Existing methods often fail to effectively handle dynamic policies, resource allocation, and scalability. this project presents a robust framework leveraging machine learning (ML) techniques integrated with NS2 simulation to address these challenges. Data collection from network nodes is the first step in the process. Preprocessing is then done to manage missing values, eliminate noise, and normalize the data for model training. Supervised learning methods like regression and classification optimize traffic prediction and routing protocols, while unsupervised techniques, including clustering, identify resource patterns for better allocation. Reinforcement learning dynamically adjusts policies to improve fault tolerance and resource management. NS2 simulation validates the model’s effectiveness across various network scenarios.A remarkable accuracy of 98.77% and a minimal error rate of 1.22% are attained by the claimed framework. © 2025 IEEE.

关键词： Self-supervised learning

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Design and realization of distributed Rule Engine for scene linkage of internet of things 6

Design and realization of distributed Rule Engine for scene ...

引用

6th international conference on internet of things, Automation and Artificial Intelligence, IoTAAI 2024

作者： Wang, Shuai Mei, Linhui Tao, Yong Tong, Chao Changjiang Schinta Software Technology Co. Ltd. Hubei Wuhan China

ISBN: (纸本)9798350386974

With the continuous expansion of the application scenarios of the internet of things (IoT), it has been getting increasingly demanding for the intelligence and automation of the IoT system. Under this circumstance, a powerful Rule Engine (RE) can realize the intelligent control, automated decision-making, and data analysis of this system, improving its efficiency and performance. the IoT involves a great number of devices, sensors and data to be processed and analyzed. In this case, a useful RE is needed to support multiple rule types and conditions, enabling it to realize the real-time data analysis, event triggering and response, and automated control and *** this paper, we proposed a better method to build a high-availability and high-adaptability RE in complex and diverse business scenarios, breaking the traditional RE as a rule flow container. By optimizing the structure, the RE is transformed from a container into a service flow. the rule flow is also defined as a scenario, making the inter-scenario linkage model get closer to various real business scenarios. © 2024 IEEE.

关键词： distributed Rule Engine internet of things Scene linkage

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Hierarchical Federated Learning for internet of Vehicles Networks: A Multi-Tiered Approach to Efficient and Adaptive distributed Learning 6

Hierarchical Federated Learning for Internet of Vehicles Net...

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6th international conference on Sustainable Technologies for Industry 5.0, STI 2024

作者： Protim, Joy Sharmin, Zeseya Sultana, Babe Green University of Bangladesh Department of Computer Science and Engineering Bangladesh School of Information Technology Deakin University Melbourne Australia

ISBN: (纸本)9798331531973

the internet of Vehicles IoV) has emerged as a critical paradigm in intelligent transportation systems, generating vast amounts of data that can be leveraged for various applications. However, the distributed nature of vehicular networks, privacy concerns, and the non-IID (non-independent and identically distributed) characteristics of the data pose significant challenges to traditional machine learning approaches. this paper proposes a novel Hierarchical Federated Learning (HFL) architecture for IoV networks, introducing an intermediate tier of regional cloud servers between vehicles and the central server. Our approach addresses key challenges in communication efficiency, data heterogeneity, and model performance. Experimental results demonstrate that HFL achieves up to 30% reduction in communication overhead and a 15% improvement in model accuracy compared to conventional federated learning methods in IoV scenarios. © 2024 IEEE.

关键词： Self-supervised learning

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Adopting Quality Attributes Based Quantitatively Methodology Using Deep Learning to NoSQL Databases 6

Adopting Quality Attributes Based Quantitatively Methodology...

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6th international conference on computing and Informatics, ICCI 2024

作者： Bayomy, Noha Ahmed Idrees, Amira M. Khedr, Ayman E. Department of Information Systems Faculty of Computers and Artificial Intelligence Helwan University Cairo Egypt Department of Information Systems Faculty of Computers and Information Technology Future University in Egypt Cairo Egypt Department of Information Systems College of Computing and Information Technology at Khulais University of Jeddah Jeddah21959 Saudi Arabia

ISBN: (纸本)9798350373875

Nowadays, Businesses are mutating to social media platforms and websites as a new source of information and knowledge to get competitive advantages. Hence, the term NoSQL databases known as internet era databases revealed as a solution because of raising urgency in the demand for scalability and performance. this paper presents an overview study for the evolution of databases, different forms of NoSQL databases in addition to their features, advantages and disadvantages. this paper also seeks to cover the shortage of focusing on the quality attributes based methodologies to NoSQL databases that have been largely overlooked in the previous studies and creates a brief comparison that illustrates this issue. © 2024 IEEE.

关键词： Competition

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