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Implementation of IoT Security System by Incorporating Block Chain technology

Implementation of IoT Security System by Incorporating Block...

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Smart Data Intelligence (ICSMDI), international conference on

作者： Arepalli Gopi Nedunuri Madhu Venkata Sai Daswanth S.S. Aravinth P.V.Siva Rambabu Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram AndhraPradesh India

internet of Things (IoT) allows both physical and virtual objects to communicate with each other over a network. The services provided with IoT helps in easing the day-to-day activities. IoT has numerous advantages like scalability and ease of access but the drawback of the IoT system is that a centralized cloud is required for data storage and ensure the security and privacy of the users. In order to eliminate the drawback of IoT, recent studies have highlighted the integration of IoT systems with the distributed ledger technologies like Blockchain. The Blockchain technology would provide military grade security to the data. This article presents a comprehensive literature review for the internet of Things (IoT) and Blockchain protocols.

关键词： Data privacy Cloud computing distributed ledger Scalability Bibliographies Smart contracts Memory

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Traffic accident data analysis based on internet of Things and cloud computing technology 22

Traffic accident data analysis based on Internet of Things a...

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3rd Asia-Pacific conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Jiang, Qiuming Li, Song Hubei Industrial Polytechnic Shiyan442000 China

ISBN: (纸本)9781450395786

The rational application of cloud computing technology and IoT technology can realize the correlation of information, time and space, effectively play a role in the field of data mining, and play an important role in traffic accident statistical analysis, accident prevention and control. The existing statistical analysis technology of road traffic accidents has some problems, such as lack of data field, single analysis dimension and weak practical application, which is difficult to support the proposal of improvement countermeasures of traffic safety system;Moreover, the complex data generated by the IoT is lack of effective management methods. technology provides ideas to solve these problems. Firstly, the traffic accident information elements are subdivided, and the road traffic accident data collection items oriented to accident cause analysis are optimized. Secondly, a dynamic analysis model of GIS accident-prone points and segments based on the severity of accidents is proposed, and a multi-dimensional analysis method of accident causes for different subjects of people, vehicles, roads and environment and different stages of accidents is established. Based on the relationship between data mining and IoT, a distributed execution method of data mining algorithm based on the concept of IoT is discussed. This method allows the data mining algorithm to be decomposed into participants and executed in a distributed environment. The proposed model improves the performance of data analysis and reduces the network traffic between terminal equipment and cloud. Data mining technology is applied to sort out and analyze road traffic accident data. © 2022 ACM.

关键词： Data mining

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Architecture Design of Electronic Commerce System Based on distributed technology

Architecture Design of Electronic Commerce System Based on D...

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Computer, Control and Robotics (ICCCR), international conference on

作者： Haiyan Suo Tao Chen Jiangsu Provincial People's Hospital Nanjing Jiangsu China JKPMG Information Technology Services (Nanjing) Co. LTD Nanjing Jiangsu China

Because of the small number of users, low concurrency and small amount of data in the early electronic commerce system, the application software only needs to deploy a single server to meet the throughput requirements. With the continuous growth of user scale and business volume, enterprises gradually adopt distributed architecture to improve the availability of electronic commerce system, and use multiple cheap machines to complete complex computing or storage tasks. In recent years, with the continuous maturity and development of cloud native technologies such as microservice technology and container cluster management technology, major internet companies have followed the ‘big middle platform strategy’ and built 'cloud platforms' that adapt to their own organizational structures to cope with market changes and make flexible and rapid strategic adjustments. In general, the main driving factor of electronic commerce system evolution is the huge number of users faced by products. Cloud native is an extension of distributed architecture. This paper introduces the development stage of software distributed architecture, designs and implements distributed electronic commerce system.

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

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

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Advance computing and Innovative Technologies in Engineering (ICACITE), international conference on

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

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.

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Performance Analysis of LBT Cat4 Based 5G IoT Enabled New Radio in Unlicensed Spectrum 1

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4th international conference on Advances in distributed computing and Machine Learning, ICADCML 2023

作者： Shaban, Zubair Gupta, Nishu Kumar, Krishan Sarowa, Sandeep Kumar Derawi, Mohammad Department of Electronics and Communication Engineering IIIT Delhi New Delhi India in Gjøvik Gjøvik Norway Department of Electronics and Communication Engineering National Institute of Technology Hamirpur Hamirpur India Scientist at Cert-In MeitY Government of India New Delhi India

ISBN: (数字)9789819912032

ISBN: (纸本)9789819912025

5G internet of Things (5G IoT) which is currently under development by the 3rd Generation Partnership Project (3GPP) envisages the way for a diversity of connecting devices to the IoT via cellular networks. As the amount of licensed spectrum is scarce in nature, New Radio Unlicensed (NR-U) is seen as a favorable solution for meeting the exponential growth in traffic demands. 5G NR-U combines the features from License Assisted Access (LAA) and 5G NR to support global cellular operations over entire possible unlicensed bands. As spectrum efficiency is an important metric in 5G communication networks, there is a need to operate in unlicensed spectrum efficiently. In this paper we adhere to Listen Before Talk (LBT) mechanism as defined by the 3GPP. Using this mechanism, NR-U will allow network terminals to use unlicensed spectrum with fair coexistence with Wi-Fi, which is an incumbent wireless technology in unlicensed spectrum. Furthermore, we propose collision avoidance technique among NR-U and other incumbent radio access technologies, better channel efficiency and high Jain’s Fairness index algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： internet of things

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Research on distributed Storage Algorithm for Multi-Source Survey Data in Power Grid Engineering

Research on Distributed Storage Algorithm for Multi-Source S...

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Artificial Intelligence, internet of Things and Cloud computing technology (AIoTC), international conference on

作者： Jiyong Zhang Gao Yu Donghui Liu Xiaohu Sun Jiangqian Huang Bangzheng He State Grid Economic and Technical Research Institute Co. State Grid Corporation of China Beijing China Economic and Technical Research Institute of State Grid Zhejiang Electric Power Co. State Grid Corporation of China Zhejiang China School of Geomatics and Urban Spatial Information Beijing University of Civil Engineering and Architecture Beijing China

ISBN: (数字)9798331530280

ISBN: (纸本)9798331530297

With the rapid development of power grid engineering, especially the rapid development of extra-high voltage engineering, the multi-source heterogeneous investigation data is on the increase, and the traditional investigation data storage methods can no longer meet the basic needs. Based on this situation, this paper adopts the consistent hash algorithm to achieve horizontal elasticity expansion of the storage system, and combines the virtual nodes of consistent hash with the weighted polling algorithm to improve the storage strategy of distributed file system (HDFS) under the Hadoop platform, to achieve balanced effect of distributed data storage. Experimental results show that the distributed storage algorithm for heterogeneous survey data from multiple sources proposed in this paper reduces the cluster load difference to different degrees under different conditions, and shows better load balance performance compared to HDFS and ordinary consistent hashing algorithms, which proves that the algorithm can effectively reduce the load difference between cluster nodes and satisfy the needs of distributed storage of power grid engineering survey data.

关键词： Surveys File systems Clustering algorithms distributed databases Memory Voltage Power grids Resource management internet of Things Faces

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Application and Evaluation of Real-Time Analysis Algorithms in Dynamic Data Processing Systems

Application and Evaluation of Real-Time Analysis Algorithms ...

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Integrated Circuits and Communication Systems (ICICACS), IEEE international conference on

作者： Si Chen College of Digital Business Liaoning Vocational University of Technology Jinzhou Liaoning China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Dynamic data processing systems are key technologies in modern data-driven applications, widely used in fields such as the internet of Things, finance and healthcare. This study explores the application and evaluation of real-time analytical algorithms for dynamic data processing. An efficient algorithmic framework combining adaptive windowing, incremental learning and distributed computing is proposed to achieve low-latency and high-accuracy decision-making capabilities. Through experimental validation in a real data streaming environment, the results show that the proposed algorithm significantly outperforms traditional algorithms with about 35% reduction in latency and 20% improvement in prediction accuracy. The research results in this paper show that the real-time analysis algorithm has a promising application in dealing with dynamic heterogeneous data streams. Meanwhile, the article also discusses the limitations and future optimisation directions of the method, which provides a reference for further research in related fields.

关键词： Performance evaluation Incremental learning Accuracy Heuristic algorithms Data processing Prediction algorithms Real-time systems Low latency communication distributed computing Streams

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Deploy a Secure Chat Application for Log Monitoring in Kubernetes

Deploy a Secure Chat Application for Log Monitoring in Kuber...

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Intelligent Data Communication Technologies and internet of Things (IDCIoT), international conference on

作者： Dinesh S R Nivedha Mahalakshmi S B Balasaigayathri Department Of CSE Cyber Security Sathyabama Institute of Science and Technology Chennai India School of computing Sathyabama Institute of Science and Technology Chennai India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

This paper presents the development and deployment of a secure chat application in a Kubernetes environment for real-time log monitoring and communication. The research addresses the challenges of managing and aggregating logs in a distributed, containerized environment, specifically within Kubernetes clusters. Traditional logging solutions often struggle with providing real-time collaborative troubleshooting, centralized log aggregation, and robust security. The proposed system integrates Kubernetes-native features, along with Fluentd and the ELK stack (Elasticsearch, Logstash, Kibana), to centralize log management and provide a unified interface for real-time communication through WebSockets. The application is designed to ensure high scalability, fault tolerance, and security by implementing TLS encryption and Role-Based Access Control (RBAC). The outcome is a scalable, secure, and efficient log monitoring solution that improves operational efficiency, enhances system reliability, and fosters collaborative debugging, making it a valuable tool for developers and administrators in Kubernetes-based environments.

关键词： Access control Sockets Scalability Collaboration Serverless computing Real-time systems User experience Encryption Monitoring Standards

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Scheduling in Cloud of Things: An Overview

Scheduling in Cloud of Things: An Overview

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Emerging Smart Technologies and Applications (eSmarTA), international conference on

作者： Abdulrahman Mohammed Hussein Obaid Awadh Ali Abdo Mohammed Santosh K. Pani Ayman Alsabry Hamzah Ali Qasem Department of Medical Information Technology 21 September University of medical and applied sciences Sana'a Yemen Department of Bioedical Engineering Technology 21 September University of medical and applied sciences Sana'a Yemen School of Computer Engineering KIIT University Bhubaneswar India Department of Computer Science International University of Technology Twintech Sana'a Yemen International University of Technology Twintech 21 September university of medical and applied sciences sana'a Yemen

computing, internet, digital devices, smart devices, and other technologies were leading to a new terminology known as cloud of things (CoT). Cloud of Things is a powerful technology used to analyze and store massive data from thousands of distributed devices (smartphones, vehicles, home appliances, sensors, etc.). Further, Cloud of Things integrated two concepts, internet of Things and Cloud computing. There are many issues in cloud computing that have been widely studied, such as scheduling. On the other hand, a few issues have been studied in Cloud of Things. The objective of this paper is to discuss and classify the scheduling issues in Cloud of Things. Researchers have developed algorithms for different environments such as heterogeneous/homogeneous clusters, cloud computing, and large-scale community grids. By reviewing and considering many of these articles, we provided an overview for reuse these state-of-the-art algorithms in Cloud of Things environments. In addition, this paper provides researchers with ideas and platform for finding open research and exploring Cloud of Things issues.

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A Multi-Task Optimization-based Heterogeneous Expensive Multi-Objective Evolutionary Algorithm

A Multi-Task Optimization-based Heterogeneous Expensive Mult...

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Artificial Intelligence, internet of Things and Cloud computing technology (AIoTC), international conference on

作者： Chunlin He Yong Zhang School of Information and Control Engineering China University of Mining and Technology Xu Zhou China

ISBN: (数字)9798331530280

ISBN: (纸本)9798331530297

Multi-objective optimization problems with different evaluation costs for performance metrics or objective values are commonly seen in the real world. Such problems are known as heterogeneous expensive multi-objective optimization problems (HE-MOPs). Although there are some researches available, the heterogeneity among objectives can cause search bias, which affects the performance of these methods on HEMOPs. To address this, we propose a Multi-Task Optimizationbased Heterogeneous Expensive Multi-Objective Evolutionary Algorithm (MT-HEMOEA). This algorithm firstly uses a multilayer sampling method based on objective evaluation costs to obtain a uniformly distributed sample set on objectives space. Then we employ multi-task exploitation strategy focused on convergence and multi-task exploration strategy focused on diversity to reduce search bias and improve sample diversity. Experimental results on WFG test problems show that the proposed algorithm achieves higher-quality optimal solution sets compared to four existing heterogeneous multi-objective optimization algorithms.

关键词： Measurement Costs Evolutionary computation Multitasking Search problems Sampling methods Nonhomogeneous media internet of Things Optimization Convergence

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