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检索条件"任意字段=3rd International Conference on Distributed Computing and Internet Technology"

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2024 3rd international conference on Artificial Intelligence, internet of Things and Cloud computing technology, AIoTC 2024

2024 3rd International Conference on Artificial Intelligence...

引用

3rd international conference on Artificial Intelligence, internet of Things and Cloud computing technology, AIoTC 2024

ISBN: (纸本)9798331530280

The proceedings contain 81 papers. The topics discussed include: research on distributed computing power scheduling based on ant path optimization;facial expression recognition in museum settings using an enhanced residual networks;LSD3K: a benchmark for smoke removal from laparoscopic surgery images;enhancing single image de-raining with a sparse spatial transformer;research on image recognition and intelligent management of accounting bills based on information technology;cloud-based flight test data management and application platform;design and simulation of biped robot based on ball screw;thinking about anti-drone strategies;RGembed: a knowledge graph embedding model integrating dual-prediction and graph attention networks;and improving the CodeGeeX model based on the relative convolutional multi-head attention method.

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A Secure distributed Estimation Based on Affinity 3

A Secure Distributed Estimation Based on Affinity

引用

3rd international conference on Artificial Intelligence, internet of Things and Cloud computing technology, AIoTC 2024

作者： Ren, Xiaoping Yi, Hao Yi, Honghua He, Yilin Southwest University College of Artificial Intelligence Chongqing China

ISBN: (纸本)9798331530280

This paper explores the issue of secure distributed estimation in the presence of attacks. Due to the presence of attacks, compromised nodes send erroneous information to their neighboring nodes, leading to a decline in network performance. Here, a distributed diffusion least-mean-square (DLMS) algorithm with affinity is proposed. The proposed algorithm uses affinity for secure distributed estimation. Specifically, we propose a distributed discrimination mechanism based on affinity to distinguish between normal nodes and malicious nodes. Simulations are conducted to demonstrate the superiority of the proposed DLMS-Affinity algorithm in comparison to other algorithms. © 2024 IEEE.

关键词： Diffusion least-mean-square (DLMS) distributed estimation Relationship mapping attributes secure estimation

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An Implementation of Photovoltaic Solar Panel Monitoring System Based on internet of Things 3

An Implementation of Photovoltaic Solar Panel Monitoring Sys...

引用

3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Saranya, J. Divya, V. School Of Computing Sciences Vels Institute Of Science Technology & Advanced Studies Chennai India School Of Computing Sciences Vels Institute Of Science Technology & Advanced Studies Department Of Information Technology Chennai India

ISBN: (纸本)9798350318609

The internet of Things (IoT) is a contemporary technology that enhances user experience and adds intelligence to objects. Numerous applications have already embraced the internet of Things. The internet of Things (IoT) has greatly simplified and increased the accessibility of our lives. Society will be better equipped to safeguard future generations by reducing greenhouse gas emissions and ozone depletion as long as everyone uses renewable energy. These PV technologies are growing in popularity because they are so widely available, reasonably priced, and easy to install and maintain. Monitoring is required to determine the current condition of each solar photovoltaic cell in a solar panel. This monitoring is necessary to detect any defects in the solar cell and implement repair actions in addition to guaranteeing that the solar panel continues to function properly. In this study, an internet of Things-based solar panel monitoring system is implemented, and the MPPT algorithm is used to track maximum power. © 2024 IEEE.

关键词： Liquid crystal displays

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An Edge computing Framework for Data Analysis in Intelligent Transportation Systems 3

An Edge Computing Framework for Data Analysis in Intelligent...

引用

3rd international conference for Innovation in technology, INOCON 2024

作者： Sharma, Sumit Bali, Rasmeet Singh Chandigarh University Computer Science Engineering Punjab India

ISBN: (纸本)9798350381931

Intelligent Transportation Systems (ITS) have been identified as a key application of the internet of Things (IoT). In order to reduce latency and bandwidth needs, edge computing offers a distributed computing architecture that can process and analyse data closer to the source. In this paper, we propose an edge computing framework for data analysis in ITS and present experimental results to evaluate its performance. The proposed framework aims to address the challenges associated with traditional data analysis techniques by leveraging the power of distributed computing resources, advanced analytics, and real-time processing capabilities. The rationale behind the framework's design and architecture is to improve the efficiency, scalability, and adaptability of ITS solutions, ensuring faster decision-making, reduced latency, and enhanced overall transportation performance. © 2024 IEEE.

关键词： Edge computing

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Enhancing internet-based Resource Discovery: The Efficacy of distributed Quadtree Overlay 3

Enhancing Internet-based Resource Discovery: The Efficacy of...

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3rd international conference on Applied Artificial Intelligence and computing, ICAAIC 2024

作者： Alqaraleh, Muhyeeddin Zarqa University Faculty of Information Technology Department of Software Engineering Zarqa13110 Jordan

ISBN: (纸本)9798350375190

distributed systems based on the internet allow resources widely dispersed throughout the network to be utilized cooperatively and shared. This allows the end-user to obtain massive computational power to perform a computationally intensive task. This is where the essential function of resource finding comes into play. Even though different procedures have been presented to identify multi-attribute resources, these processes have been plagued by many problems, including significant overhead and inefficiency as the number of resources increases. distributed Quadtree Overlay is the innovative technology presented in this academic study. With DOTO, distance-aware querying is used. Moreover, since DOTO is constructed via the local network, it does not need any communication. As a result of the trials, the distributed Quadtree Overlay performed better than the Chord. According to the findings, distributed Quadtree Overlay is superior to Chord in terms of communication time since it needs fewer hopes and messages, uses less memory, and produces better (shortened) communication times. © 2024 IEEE.

关键词： distributed computer systems

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An Authentication Scheme with Attribute-Based Encryption for Power internet of Things 24

An Authentication Scheme with Attribute-Based Encryption for...

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3rd international conference on Networks, Communications and Information technology (CNCIT)

作者： Duan, Xiangjun Li, Yunshuo Xu, Yuanyuan Liu, Wei Zhang, Zhengkai Liu, Lei Li, Ying Xu, Mengyu China Elect Power Res Inst Beijing Peoples R China State Grid Anhui Elect Power Co Ltd Elect Power Res Inst Hefei Peoples R China State Grid Anhui Elect Power Co Ltd Hefei Peoples R China Shanghai Wudun Informat Technol Co LTD Shanghai Peoples R China

ISBN: (纸本)9798400717048

Power internet of Things(PIot) has absorbed edge computing technology, reducing the computing pressure of cloud service centers and providing intelligent services for edge devices through edge server. Due to the computing resources constraints,unattended and widely distributed of end devices,attacks on edge devices and edge servers are becoming more ***-based encryption can provide a higher level of protection for the edge computing model and a more flexible operation relationship. In the current attribute-based encryption scheme, the attributes assigned by the cloud server to the edge device are not authenticated, which may lead to the situation that the assigned attributes are stolen. we propose an identity authentication scheme that can authenticate for attributes. The scheme realizes mutual authentication between edge devices and edge servers. It combines attributes and ID to authenticate, thereby avoiding the misuse of attributes. This scheme can provide higher security without affecting the efficiency.

关键词： Power internet of things edge computing identity authenticate for attributes attribute-based encryption

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The Application of Artificial Intelligence and internet of Things technology in Equipment Control Management Systems 3

The Application of Artificial Intelligence and Internet of T...

引用

3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Du, Jinqi Yang, Chuan Liu, Ye College Of Mechanical And Power Engineering Shenyang University Of Chemical Technology Liaoning Shenyang China

ISBN: (纸本)9798350318609

In many fields, equipment control management systems are often used. The main purpose is to monitor and manage various types of equipment and software systems required for work, aiming to improve the efficiency and maintainability of equipment, thereby achieving effective management of equipment. Therefore, this article further proposes to use artificial intelligence and the internet of Things to design an equipment control management system to achieve more efficient equipment management. Finally, this article completed the verification of the effectiveness of the method in this article through comparative experiments. In a comparative experiment on work efficiency improvement between the equipment control management system based on the method in this article and the conventional system, the average work efficiency of the former was improved to 83.30%, while the work efficiency of the latter was improved to 60.29%. It can be seen from the experimental results that artificial intelligence and the internet of Things are indeed very suitable for establishing equipment control management systems. © 2024 IEEE.

关键词： Artificial intelligence

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Short Term Nonlinear Load Forecasting Method for distributed Photovoltaic Grid Connection Based on GSA Algorithm 3

Short Term Nonlinear Load Forecasting Method for Distributed...

引用

3rd international conference on Artificial Intelligence, internet of Things and Cloud computing technology, AIoTC 2024

作者： Xu, Pengfei Li, Yan Tang, Mengyuan Tian, Xing Gao, Baohao Economic and Technological Research Institute of State Grid Ningxia Electric Power Co. Ltd. Yinchuan Ningxia750004 China

ISBN: (纸本)9798331530280

In order to cope with the intermittency and uncertainty of photovoltaic power generation and improve the accuracy of short-term load forecasting, a distributed photovoltaic grid connected short-term nonlinear load forecasting method based on Genetic Simulated Annexing Algorithm (GSA) is proposed. The historical data of the distributed photovoltaic grid connected system is used as the analysis basis, and the concept of particle aggregation is introduced to establish a solution space. The global load data is searched in the space, and the original data is substituted into the solution space to achieve load data normalization processing. Design a distributed photovoltaic grid connected short-term nonlinear load forecasting method based on GSA, obtain the global optimal solution, and accurately predict short-term load changes. The experimental results show that this method has significantly improved prediction accuracy and can more accurately predict short-term nonlinear loads. © 2024 IEEE.

关键词： distributed photovoltaic grid connected system Genetic simulated annealing algorithm Load data preprocessing Short term nonlinear load

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An IoMT Framework Integrating 5G and Wireless Body Area Networks for Home Healthcare 24

An IoMT Framework Integrating 5G and Wireless Body Area Netw...

引用

3rd international conference on Networks, Communications and Information technology (CNCIT)

作者： Zhang, Chongqing Su, Lihui Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao Peoples R China Heze Univ Coll Comp Sci & Engn Heze Peoples R China

ISBN: (纸本)9798400717048

The rapid development of computer technology, communication technology, network technology and sensor technology has led to the birth of the internet of Things (IoT). Applying IoT to the field of medical care has given rise to the internet of Medical Things (IoMT). With IoMT, it is feasible to provide a new home health care model for the elderly and those who do not have convenient access to hospitals for medical services. In this paper, an IoMT-based framework with five layers is designed to provide adequate healthcare services to the elderly people. Wireless body area networks (WBANs) are adopted to address the long-term continuous monitoring issue. Deep learning and federated learning are used to process the collected data to obtain knowledge and models. 5G is employed to transmit the emergent data and models quickly. Cloud computing, edge computing and fog computing are collaboratively used to design an architecture for federal learning process. By integrating all the techniques, the framework can provide an adequate computing platform for the healthcare work of the elderly people.

关键词： internet of Medical Things (IoMT) 5G Smart Health Care Wireless Body Area Networks (WBANs) Cloud computing Edge computing Big Data

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An Adaptive Task Scheduling Approach for Cloud computing Using Deep Reinforcement Learning 3

An Adaptive Task Scheduling Approach for Cloud Computing Usi...

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3rd international conference on distributed computing and High Performance computing, DCHPC 2024

作者： Amini, Pedram Kalbasi, Amir Amirkabir University of Technology Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350381580

Today, many important internet services are provided on cloud computing platforms. The ever-increasing expansion of services and user requirements has necessitated the optimal use of resources. Therefore, several algorithms for optimal resource usage have been proposed to increase cloud performance and provide more satisfactory services to internet users. Typically, each algorithm is suitable for a specific environment, and their performance is affected by changes of the execution environment. Meanwhile, the assignment of tasks to resources in cloud computing is a difficult problem that NP-Complete. This paper proposes a novel deep reinforcement learning-based approach for task scheduling in cloud computing environments, aiming to minimize the makespan, which is the total time required to complete all tasks. The proposed approach utilizes a deep Q-learning algorithm to learn the near-optimal task allocation strategies based on the current state of the system. The task scheduling performance of the proposed approach is compared with the Min-Min, Min-Max, FCFS and GA algorithms based on three criteria: makespan, algorithm execution time, and computational complexity. Simulation results demonstrate that the proposed approach results in excellent makespan, while demonstrating very small algorithm execution time. © 2024 IEEE.

关键词： Reinforcement learning

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