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

共 8188 条记录，以下是51-60 订阅

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Research on Storage and Query Optimization Algorithm of distributed Database for Big Data 3

Research on Storage and Query Optimization Algorithm of Dist...

引用

3rd international conference on Data Analytics, computing and Artificial Intelligence, ICDACAI 2024

作者： Liu, Lixia College of Information Engineering Engineering University of PAP Shaanxi Xi'an710086 China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519032

This paper deeply discusses the storage and query optimization algorithm of distributed database for big data. Firstly, the importance of distributed database storage optimization is analyzed, and key technologies such as column storage technology, data backup and consistent hash algorithm are introduced. Then, the distributed database query optimization algorithm is mainly studied, and an innovative algorithm combining semi-join, direct join and hash partition equijoin strategy is proposed, and the query plan is dynamically adjusted by introducing an intelligent prediction model to maximize the query performance. The experimental results show that the algorithm has significantly improved the storage efficiency and query performance, which proves its effectiveness and application prospect in the big data environment. Future research will focus on further improving the adaptability and generalization ability of the algorithm to cope with more complex data scenarios and query requirements. © 2024 IEEE.

关键词： Structured Query Language

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Securing the internet of things communication and data transmission by using Blockchain based Architecture 3

Securing the internet of things communication and data trans...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Sheetal Kumari, Vasantha Badiger, Veena S Presidency College Department of Computer Applications Bengaluru India

ISBN: (纸本)9798331515911

Due to the rapid growth of technology usage of internet of Things devices has revolutionized in multiple domains and areas, but still there are few challenges to address like security and performance issues. Most of the traditional approaches are not sufficient in solving those issues related to IoT ecosystems. This paper aims to present a block chain technology-based solution to the problems of security challenges and improvement in integrity, confidentiality, and availability for IoT systems. The features of Block chain in the sense of an immutable nature help secure the IoT system to share data with others, enhance authentication, and transparency. The integration of block chain with IoT devices can also ensure data provenance thus creating an environment for trust with users and stakeholders. To build this blockchain-based IoT system, the proposed architecture ensures a framework of not only ensuring the security of the IoT ecosystem but also sustainability. Future work will be based on designing prototypes and applications within real-world environments to validate the effectiveness of these proposed solutions in various IoT scenarios. © 2025 IEEE.

关键词： Blockchain technology challenges IoT architecture security

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BOA-LSSVM Network-Based Malware Detection with Combination Weighting 3

BOA-LSSVM Network-Based Malware Detection with Combination W...

引用

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

作者： Hu, Ruijie Beijing Normal University Hong Kong Baptist University United International College Guangdong Province Zhuhai China

ISBN: (纸本)9798331530280

With the rapid development of the internet, network malware such as viruses, worms, and trojans has become increasingly complex and covert, posing significant threats to information security for individuals, businesses, and nations. Traditional malware detection methods rely on feature signatures or rule-based systems, which struggle to address novel and unknown threats and are often bypassed. Technologies like machine learning are extensively used in cybersecurity for automating the detection of network malware and examining unsafe factors during internet usage. Addressing these issues, this paper proposes a BOA-LSSVM network malware detection method based on combination weighting, which leverages the advantages of optimization algorithms and machine learning. Experiments conducted on real-world datasets demonstrate that this method outperforms traditional approaches in terms of accuracy, precision, recall, and F 1 score. The effectiveness of this method has been validated, providing an effective technological means to enhance network security. The results of this research are expected to significantly advance the field of cybersecurity. © 2024 IEEE.

关键词： Cyber attacks

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Stability of Knowledge-Sharing Alliances in distributed computing Systems: An Evolutionary Game Theory Approach 24

Stability of Knowledge-Sharing Alliances in Distributed Comp...

引用

3rd international conference on Artificial Intelligence and Intelligent Information Processing, AIIIP 2024

作者： Yi, Fei Liang, Yangyang Long, Zhaoyang School of Public Administration Xiangtan University Hunan Xiangtan China School of Humanities and Law Jiangsu Ocean University Jiangsu Lianyungang China

ISBN: (纸本)9798400707308

In this paper, evolutionary game theory is used to study the boundary conditions of different stable states of knowledge alliances in distributed computing environments and the specific factors that influence the evolution of unstable alliances. The paper demonstrates the symbiotic relationship between members of a knowledge alliance and the applicability of evolutionary game methods, defines the boundary conditions of three different states of knowledge alliances (stable, unstable and dissolved), and reveals the determinants that lead unstable alliances to reach a stable state. This research provides a reference for the development of better distributed computing systems. © 2024 Copyright held by the owner/author(s).

关键词： Cooperation Stability

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Caching Techniques in Edge computing and Challenges 3

Caching Techniques in Edge Computing and Challenges

引用

3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Kumar, Sumit Dash, Yajnaseni Galgotias University Department of Computer Science & Engineering Uttar Pradesh India School of Computer Science Engineering and Technology Bennett University Uttar Pradesh India

ISBN: (纸本)9798350330724

Edge computing, a distributed computing concept, brings data processing and storage closer to endpoints or edge devices. Caching methods are crucial in edge computing environments for optimizing performance and minimizing latency and enable faster response times, efficient bandwidth utilization, and enhanced scalability. Edge computing uses caching techniques strategically based on user behaviour studies and access patterns to boost scalability and reduce network congestion. Caching techniques increase the efficacy and performance of edge computing. The parameters that influence efficacy include cache management strategies, network conditions, application features, and data access patterns. This paper presents a brief overview of the caching technologies utilized in edge computing and their challenges. © 2023 IEEE.

关键词： internet of things

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Automated Cybersecurity Attack Detection Using Prairie Dog Optimization and Multilayer Perceptron in Healthcare System 3

Automated Cybersecurity Attack Detection Using Prairie Dog O...

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

作者： Pillai, Sanjaikanth E. Vadakkethil Somanathan Poddar, Sanjay Susanta Nagendar, Y. Pareek, Piyush Kumar Zanke, Pankaj School Of Electrical Engineering And Computer Science University Of North Dakota Grand Forks United States Fortinet Ltd DallasTX United States School Of Computer Science And Engineering Sr University Telangana Warangal India Nitte Meenakshi Institute Of Technology Department Of Aiml And Ipr Cell Bengaluru India Sapiens International Corporation United States

ISBN: (纸本)9798350318609

internet of Things (IoT) technologies have become an inevitable part of our lives with many innovations and conveniences in many fields such as education, healthcare, social life and security. While healthcare network complexity and connectivity are developing in a superior manner at the same time, cyber-attack surfaces and vulnerabilities are also increasing dramatically. Harming people either physically or digitally are some of the threat to the health and life of patients through data breaches across multiple departments of health systems. In this research, the prairie dog optimization (PDO) algorithm and multilayer perceptron (MLP) is proposed cyber-attack detection model. The proposed approach was performed the several IoMT cybersecurity datasets using Intensive Care Unit (ICU Dataset), Washington University in St. Louis enhanced healthcare monitoring system (WUSTL-EHMS) datasets, Edith Cowan University- internet of Health Things (ECU-IoHT), and TON-IoT. PDO is used for selecting the optimal features from the attained dataset, MLP parameters is performed by hyperparameter optimization as well as 10-fold cross-validation technique for performance assessment. The proposed method has the potential to counter cyber-attacks in healthcare applications, it attained higher precision at 99.54%, accuracy of 99.45%, recall 99.56% and f1-score 99.46% in ECU-IoHT dataset. © 2024 IEEE.

关键词： internet of things

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Supply Chain Management Growth With the Adoption of Blockchain technology (BoT) and internet of Things (IoT) 3

Supply Chain Management Growth With the Adoption of Blockcha...

引用

3rd international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Singh, Gaurav Kumar Dadhich, Manish Sir Padampat Singhania University Research Scholar Udaipur India Sir Padampat Singhania University School of Management Udaipur India

ISBN: (纸本)9798350399264

Globalization has posed many threats to managing supply chains and logistic networks. Blockchain technology and internet of Things have outlined budding for answering global Supply Chain Management (SCM) issues. It is a distributed digital ledger platform that renders transparency, traceability, and security. This paper significantly analyzes 140 IT experts of BoT and IoT managers working in supply chain management. Smart PLS is employed, and the proposed model offers improved transparency, efficiency, security, and traceability, enabling faster decision-making, enhanced operational performance, and better collaboration among supply chain participants. As organizations increasingly recognize the benefits of BoT and IoT, we can expect to see widespread adoption and continued innovation in SCM. It is suggested that future study proposals and methods might suggest insights into overcoming supply chain obstacles. © 2023 IEEE.

关键词： internet of things

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IoT-Based Smart Energy Monitoring, Management, and Protection System for a Smart MicroGrid 3

IoT-Based Smart Energy Monitoring, Management, and Protectio...

引用

3rd international conference on Power, Control and computing Technologies, ICPC2T 2024

作者： Joha, Md. Ibne Rahman, Md Minhazur Zubair, Md. Ibna Khulna University of Engineering Technology Dept. of Electrical and Electronic Engineering Khulna9203 Bangladesh Chittagong University of Engineering Technology Dept. of Mechatronics and Industrial Engineering Chittagong4349 Bangladesh

ISBN: (纸本)9798350349207

The electric power sector is making significant changes to the power grid in order to make the power supply more stable, meet rising demand, and optimize the use of distributed generators. The internet of Things (IoT) and digital technologies are being used simultaneously in smart microgrids, a key strategy for future power grids. IoT -based smart energy monitoring and management systems are a type of technology that uses devices and software connected to the internet to monitor, control, and manage the energy use of the micro grid. In this paper, IoT-based technology is used to create a smart energy monitoring, management, and protection system for a smart microgrid. The whole system can provide real-time monitoring, control, protection, and efficient management of the microgrid's energy resources, as well as ways to detect electric theft. Using wireless communication technology, the IoT platform can send and receive measured data from the control panel room. Once access permissions to the Blynk IoT cloud software for the ESP32 and ESP8266 modules for the system are set up, micro grid operators can simply monitor all electrical parameters and control relay modules of the control panel room, electric distribution poles, and energy meters using smartphones or personal computers at any-time from anywhere. So, the IoT-based smart energy monitoring, management, and control strategy presented in this research is set up to improve energy use efficiency, reduce energy costs, and improve grid stability through real-time monitoring, control, and protection systems. © 2024 IEEE.

关键词： internet of things

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A Spatial Focal Modulation Network for Image Restoration 3

A Spatial Focal Modulation Network for Image Restoration

引用

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

作者： Yang, Lei Liu, Jingyi Shi, Ze Shi, Caijuan Li, Liqi Meng, Fanyu College of Fine Arts Capital Normal University Beijing China School of Mathematical Sciences Capital Normal University Beijing China College of Computing and Automation Wuhan Technology and Business University Wuhan China College of Artificial Intelligence North China University of Science and Technology Tangshan China Information Engineering College Capital Normal University Beijing China Luannan Area Toll Station Hebei Qiancao Expressway Development Co. Ltd. Hebei China

ISBN: (纸本)9798331530280

Deep learning methods based on CNNs and Transformers have attained notable achievements in image restoration (IR). However, CNNs have limited receptive fields, which can be a constraint in IR tasks for specific input content. The self-attention mechanism of Transformers is affected by quadratic computational complexity, making it particularly noticeable in IR tasks with high-resolution inputs. This paper proposes a Spatial Focal Modulation Network (SFMN) for IR, attempting to introduce focal modulation to replace the selfattention mechanism for modeling. Experiments on the public datasets Set5, Set14 and Urban100 show that SFMN achieves competitive results. © 2024 IEEE.

关键词： Restoration

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Analysing the Quality and Management of Data in Big Data 3

Analysing the Quality and Management of Data in Big Data

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

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

ISBN: (纸本)9798350318609

Big data analytics delves into these immense datasets to reveal hidden patterns and correlations, yet its pervasive use raises substantial security and privacy concerns. This article centers on the specific issues concerning privacy and security within the realm of big data, distinguishing between these concerns and outlining their distinct requirements. The focus is on various privacy strategies, including L-diversity, k-anonymity, HyBrEx, and T-closeness, examining their practical applications in diverse business contexts. Privacy protection methods have surfaced throughout various stages of the big data life cycle, aiming to ensure privacy during data creation, retention, and handling. This paper provides an extensive review of these privacy mechanisms while addressing the challenges encountered by current approaches. As the extended comprehensive study is experimented with features extraction techniques such as Principle component analysis (PCA), Independent component analysis (ICA), Linear discriminant analysis(LDA) the evaluated performance in terms of accuracy achieved with 98%, 99% and 95% respectively. © 2024 IEEE.

关键词： Data Analytics

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