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

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6th IFIP international conference on internet of things, IFIP IoT 2023

6th IFIP International Conference on Internet of Things, IFI...

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6th IFIP international conference on internet of things, IFIP IoT 2023

the proceedings contain 63 papers. the special focus in this conference is on internet of things. the topics include: Blockchain-Based Secure Noninvasive Glucometer and60;Automatic Insulin Delivery System for60;...

ISBN: (纸本)9783031458811

the proceedings contain 63 papers. the special focus in this conference is on internet of things. the topics include: Blockchain-Based Secure Noninvasive Glucometer and Automatic Insulin Delivery System for Diabetes Management;an Efficient and Secure Mechanism for Ubiquitous Sustainable computing System;understanding Security Challenges and Defending Access Control Models for Cloud-Based internet of things Network;fog computing in the internet of things: Challenges and Opportunities;A 2-Colorable DODAG Structured Hybrid Mode of Operations Architecture for RPL Protocol to Reduce Communication Overhead;role-Based Access Control in Private Blockchain for IoT Integrated Smart Contract;VXorPUF: A Vedic Principles - Based Hybrid XOR Arbiter PUF for Robust Security in IoMT;Easy-Sec: PUF-Based Rapid and Robust Authentication Framework for the internet of Vehicles;fortiRx: distributed Ledger Based Verifiable and Trustworthy Electronic Prescription Sharing;a Survey of Pedestrian to Infrastructure Communication System for Pedestrian Safety: System Components and Design Challenges;survival: A Smart Way to Locate Help;federated Edge-Cloud Framework for Heart Disease Risk Prediction Using Blockchain;understanding Cybersecurity Challenges and Detection Algorithms for False Data Injection Attacks in Smart Grids;comprehensive Survey of Machine Learning Techniques for Detecting and Preventing Network Layer DoS Attacks;power Analysis Side-Channel Attacks on Same and Cross-Device Settings: A Survey of Machine Learning Techniques;Lite-Agro: Exploring Light-Duty computing Platforms for IoAT-Edge AI in Plant Disease Identification;farmIns: Blockchain Leveraged Secure and Reliable Crop Insurance Management System;PTSD Detection Using Physiological Markers;a Signal Conditioning Circuit with Integrated Bandgap Reference for Glucose Concentration Measurement;detection of Aircraft in Satellite Images using Multilayer Convolution Neural Network;computer Vision Based 3D Model Floor Construction

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Digital Twin System Based on Swarm Intelligence Scheduling 6

Digital Twin System Based on Swarm Intelligence Scheduling

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

作者： Li, Qiang Zhao, Feng Zhao, Linlin Qin, Xuhong Wang, Yubo Zhu, Yana State Grid Information & Telecommunication Group Co. Ltd Beijing China Beijing State Grid Xintong Accenture Information Technology Co. Ltd Beijing China

ISBN: (纸本)9798350386974

With the large-scale integration of distributed energy resources, issues such as reverse power flow, heavy overloads in both positive and negative directions, and voltage violations have become prominent in scenarios where source-grid-load-storage collaborate and interact, such as source complementarity and source-load complementarity. It is crucial to promptly eliminate power risks and ensure the safe and stable operation of the distribution network. However, due to the complex structure, numerous devices, and large scale of the distribution network, traditional regulation and control models no longer meet the requirements of collaborative scheduling among source, grid, load, and storage. To address these issues, this paper proposes a digital twin technology based on swarm intelligence scheduling, which combines artificial intelligence large-model technology with digital twin technology to establish an interactive simulation and deduction mechanism for the distribution network's source-grid-load-storage interaction, thereby improving the quality and efficiency of collaborative scheduling among source, grid, load, and storage. © 2024 IEEE.

关键词： distributed Energy Large Model Swarm Intelligence Scheduling

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Effectiveness Evaluation of Parallel Volunteer computing 11

Effectiveness Evaluation of Parallel Volunteer Computing

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11th IEEE international conference on Consumer Electronics - Taiwan (ICCE-Taiwan) - Empower of Innovative Consumer technology

作者： Inohara, Keiichi Kurokawa, Yota Fukushi, Masaru Yamaguchi Univ Grad Sch Sci & Technol Innovat Ube Yamaguchi Japan

ISBN: (纸本)9798350386851;9798350386844

Volunteer computing (VC) is a type of network computing which exploits idle computing resources provided by vast amount of users on the internet. In our previous work, we have implemented a prototype system of parallel VC with the approach of server assisted communication and demonstrated the feasibility of parallel computing on a VC environment, not distributed computing as in the current VC. In this paper, we evaluate the effectiveness of parallel VC. the nature of nodes' volatility and unreliability in VC makes parallel computing not always effective. through the simulations using open trace data of nodes' behavior, we reveal parallelism and redundancy of job execution which minimize execution time while maintaining high degree of reliability.

关键词： volunteer computing parallel computing server assisted communication

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POSTER: IoT and Humanoid Robotics for Next Generation Motor Rehabilitation Systems 20

POSTER: IoT and Humanoid Robotics for Next Generation Motor ...

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

作者： Borgo, Stefano Di Felice, Marco Esposito, Alfonso Seidita, Valeria Spaletta, Giulia Toni, Roberto Zyrianoff, Ivan ISTC CNR Lab Appl Ontol LOA Trento Italy Univ Bologna Dept Comp Sci & Engn Bologna Italy Univ Palermo Dept Engn Palermo Italy CNR ISSMC Faenza Italy Tufts Univ Sch Med TMC Endocrinol Boston MA 02111 USA

ISBN: (纸本)9798350369458;9798350369441

the recent Covid-19 pandemic has highlighted the pressure on healthcare infrastructure, emphasizing the necessity for more tailored and sustainable healthcare systems that exploit the potential of emerging technologies such as robotics and the internet of things (IoT). In this paper, we delve into this potential by presenting I-TROPHYTS, an innovative framework designed for the real-time and semi-autonomous supervision of motor rehabilitation activities in indoor settings. I-TROPHYTS introduces a visionary approach that leverages humanoid robotics to mimic the actions of physiotherapists. this robotic system dynamically adjusts motor rehabilitation routines based on real-time performance and vital signs of groups of patients, which are monitored through wearable IoT devices. the paper introduces the I-TROPHYTS framework architecture along with its essential components. Furthermore, it elaborates on the implementation of the IoT monitoring infrastructure through the Bluetooh Mesh technology.

关键词： internet of things (IoT) Humanoid Robotics Rehabilitation Knowledge Modeling Smart Spaces

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6th IFIP international conference on internet of things, IFIP IoT 2023

6th IFIP International Conference on Internet of Things, IFI...

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6th IFIP international conference on internet of things, IFIP IoT 2023

ISBN: (纸本)9783031458774

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Research on modeling and dynamic performance simulation of distributed drive electric vehicle 6

Research on modeling and dynamic performance simulation of d...

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

作者： Liu, Qiusheng University of the East Manila Philippines Jiangxi College of Applied Technology Ganzhou China

ISBN: (纸本)9798350386974

In order to reduce the development and test costs, this paper simulates the dynamic driving performance of distributed drive electric wheel vehicles based on virtual simulation technology. the structure and characteristic parameters of distributed drive electric wheel vehicles are measured and identified by using the actual vehicle platform. A wheel hub motor characteristic measurement platform is built to complete the loading and efficiency experiments of the wheel hub motor. According to the actual vehicle parameters and motor characteristic parameters obtained, a vehicle joint simulation test platform is established based on Carsim/Simulink. the vehicle drive control strategy is designed by a hierarchical method. the upper layer uses the vehicle speed following controller to obtain the total longitudinal force demand for driving, and the lower layer uses the dynamic load distribution method to complete the reasonable distribution of the four-wheel drive torque. Finally, the established simulation model and control strategy are simulated and analyzed in terms of acceleration, braking and handling stability. the results show that the established simulation test platform and drive control strategy are accurate and effective, and can effectively simulate the driving performance of the actual vehicle platform. © 2024 IEEE.

关键词： Electric load distribution

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SAGIN-CAIN: A 3D Routing Protocol for Post-Disaster SAGIN 6G Network 20

SAGIN-CAIN: A 3D Routing Protocol for Post-Disaster SAGIN 6G...

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

作者： Marinho, Ricardo Pagoto Vieira, Luiz F. M. Vieira, Marcos A. M. Loureiro, Antonio A. F. Univ Fed Minas Gerais Dept Comp Sci Belo Horizonte MG Brazil

ISBN: (纸本)9798350369458;9798350369441

the 6G wireless networks are already being studied and their main novelties are beginning to emerge. the 6G network promises 100% network coverage in every area, including wilderness areas such as the ocean, desert, or remote areas, as it will be a fully 3D network, i.e., it will integrate space, air, and terrestrial networks. Also, with all these types of devices, the complexity of 6G networks increases, and Artificial Intelligence (AI) techniques will be mandatory for all the 6G's potential data and parameters. Hence, a Space-Air-Ground Integrated Network (SAGIN) is a potential alternative to enable all the network coverage as drones and satellites can cover large areas and fill possible network coverage gaps. the 6G network coverage also includes post-disaster regions with no network infrastructure and no network coverage, making SAGIN very suitable for them. thus, in this work, we expand CAIN, a post-disaster 6G routing protocol, so it can also be used in SAGIN scenarios, increasing even more network coverage. With drones as relays, SAGIN-CAIN routes the CAIN's Cluster Head's messages until it reaches a satellite.

关键词： 6G SAGIN RL Network coverage area

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Shrew distributed Denial-of-Service (DDoS) Attack in IoT Applications: A Survey 6th

Shrew Distributed Denial-of-Service (DDoS) Attack in IoT App...

引用

6th IFIP WG 5.5 international Cross-Domain conference on internet of things

作者： Singh, Harshdeep Baligodugula, Vishnu Vardhan Amsaad, Fathi Wright State Univ 3640 Colonel Glenn Hwy Dayton OH 45435 USA

ISBN: (纸本)9783031458804;9783031458781;9783031458774

With the rise of IoT and cloud computing, DDoS attacks have become increasingly harmful. this paper presents a survey of techniques for detecting and preventing DDoS attacks, specifically focusing on Shrew DDoS or low-rate DDoS attacks. We explore the use of machine learning for DDoS detection and prevention and introduce a new potential technique that simplifies the process of detecting and preventing DDoS attacks originating from multiple infected machines, typically known as zombie machines. As a future direction, we discuss a new technique to simplify the detection and prevention of shrew DoS attacks originating from multiple infected machines, commonly known as botnets. the insights presented in this paper will be valuable for researchers and practitioners in cybersecurity.

关键词： Shrew DoS Low-rate DDoS LDDoS Attack IOT Communication security Ns-2

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Scalable Computation Offloading for Industrial IoTs via distributed Deep Reinforcement Learning 27

Scalable Computation Offloading for Industrial IoTs via Dist...

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27th international conference on Computer Supported Cooperative Work in Design (CSCWD)

作者： Dai, Bin Qiu, Yuan Feng, Weikun Beihang Univ Int Innovat Inst Hangzhou Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China Shanghai Aerosp Elect Technol Inst Shanghai Peoples R China

ISBN: (纸本)9798350349184;9798350349191

Recent years have witnessed an increasing popularity of the internet of things (IoT), the application of which on manufacturing further triggers the emergence of Industrial IoT (IIoT), a key technology for Industry 4.0. IIoT applications tend to be computation-intensive and latency-sensitive, while IIoT devices (IIDs) are typically equipped with limited computing and energy resources. Edge computing has been envisioned as a promising paradigm to bridge the gap between IIoT applications' demands and IIDs' capabilities, by offloading computation-intensive tasks to edge servers. Hence, the development of efficient computation-offloading approaches for IIoT has attracted numerous attention recently, and many important algorithms have been proposed. However, most of the existing computation-offloading algorithms in IIoT are developed based on either centralized scheduling or fully-distributed scheduling, which could face intractable troubles in large-scale IIoT. To address the issue, this paper proposes a semi-distributed computation-offloading approach, primarily based on the designed centralized scheduling and distributed execution framework and the proposed state propagation algorithm, so that global state collection and transmission are no longer required. Experimental results show that the proposed approach could achieve similar performance to that of centralized approaches and more satisfactory performances than those of baseline approaches in various IIoT scenarios.

关键词： Edge computing internet of things industrial internet of things deep reinforcement learning

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distributed Task Offloading in Mobile Edge computing using Metaheuristics 6

Distributed Task Offloading in Mobile Edge Computing using M...

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6th international conference on Communications Signal Processing and their Applications

作者： Samarneh, Ala' A. Alma'aitah, Abdallah Y. Jordan Univ Sci & Technol Dept Network Engn & Secur Irbid Jordan

ISBN: (纸本)9798350384826;9798350384819

Mobile Edge computing (MEC) is emerging as a prominent technology that enables different sophisticated mobile applications. With the high transmission rates provided by 5G and beyond and the MEC technology, satisfying applications' strict delay requirements is possible. By providing high computation power closer to the users at the network edge, various applications such as smart cities, context awareness, and content distribution can provide users with a better Quality of Experience (QoE) using MEC. However, offloading all tasks to the MEC is inefficient, as transmitting tasks to the MEC drains the UE battery and might create congestion at the network edge. therefore, the UE must determine the subset of tasks to offload to the MEC to minimize energy consumption and execution delays. In this work, we investigate a UE-driven offloading approach utilizing three metaheuristic algorithms: Hybrid Improved Whale Optimization Algorithm (HI-WOA), Tug of War Optimization (TWO), and Adaptive Equilibrium Optimization (AEO), and priority queues. We formulate the offloading decision as a constrained multi-objective optimization problem, where the objectives are to minimize the energy consumption and execution delay at the UEs. the HI-WOA, AEO, and TWO demonstrated robust performance through extensive simulations with an average Qualified Tasks Ratio (QTR) of 99.75%, 99%, and 94% respectively, and a significant reduction in the execution delays and energy consumptions under different workloads with varying requirements.

关键词： MEC task-offloading metaheuristics

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