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Design of a Digital Twin Platform Based on distributed computing and Resource Optimization Algorithms 5th

Design of a Digital Twin Platform Based on Distributed Compu...

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5th international conference on 3D Imaging technologies—Multidimensional Signal Processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Gan, Jianxiong Kong, Fanxin Zhang, Yingqi State Grid Information & Telecommunication Group Co. Ltd. Beijing Branch Beijing100031 China

ISBN: (纸本)9789819751808

the digital twin platform builds a twin model database through data aggregation, achieving centralized storage and management of multi-dimensional, cross professional, and format normalized twin data. By associating various business and perception data and mapping relationships in the data center through the unique identification code entity ID of the model, it serves the reuse of twin data in the later stage. the research results indicate that when the resource pool or queue settings are unreasonable, some pools or queues may have idle resources, while others may be resource saturated, resulting in wasted resources and longer runtime;Reasonable configuration will greatly reduce the completion time of homework. the running time of the algorithm in this article is shorter than that of the first in, first out scheduling algorithm and the naive Bayesian classification scheduling algorithm. It can be seen that the algorithm in this article is better than both of them. the distributed computing digital twin platform needs to dynamically divide different computing domains based on the different characteristics of online and offline application functions, and develop different computing resource allocation plans to shorten the computing cycle of offline application functions as much as possible. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cloud platforms

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Improvement Method for Wide Area Low Power IoT Dedicated Communication Protocol 9

Improvement Method for Wide Area Low Power IoT Dedicated Com...

引用

9th international conference on Intelligent computing and Signal Processing, ICSP 2024

作者： Wang, Haifu Zhang, Hengbo Cheng, Hongguang Zhu, Shijian Military Science Academy National Defense Engineering Research Institute Beijing100850 China

ISBN: (纸本)9798350376548

Low power wide area internet of things (IoT) is a new type of IoT network that solves the communication needs of traditional IoT that cannot meet long-distance and low-power requirements. Low power wide area IoT compensates for the shortcomings of traditional IoT technology and wireless sensor network technology, and realizes a wider range of IoT application interconnection communication technology. Compared with existing technologies such as ZigBee, Bluetooth, 4G, 5G, etc., low-power wide area internet of things technology takes into account both medium to long-distance communication and energy consumption during the communication process. As an emerging internet of things technology, low-power wide area internet of things technology has been widely used, with a large number of technologies emerging as support for the development of the internet of things, and has rapidly developed in this field. © 2024 IEEE.

关键词： Communication protocol internet of things Long distance communication Low power consumption

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Global Identification Passport: A Unique Cloud based Passport Model 5

Global Identification Passport: A Unique Cloud based Passpor...

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5th international conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Raja, A. Ravi Anuradha, T. Majji, Sankararao Patnala, Tulasi Radhika Sushama, C. Kapila, Dhiraj Velagapudi Ramakrishna Siddhartha Engineering College Ece Department Vijayawada India Kcg College of Technology Department of Electrical and Electronics Engineering Chennai India Griet Department of Ece Hyderabad India Gitam Universirty Dept of Ece Hyderbad India School of Computing Mohan Babu University Department of Computer Science and Engineering Vijayawada India Lovely Professional University Department of Computer Science and Engineering Phagwara India

ISBN: (纸本)9781665474672

DDoS attacks pose a serious risk to cloud networks because of the money they might cost if they succeed. For this reason, the Security Research Group has been hard at work creating various detection methods to lessen the blow of any future cyberattacks. Cloud computing, often known as internet computing, is a model of delivering computing as a service, in which shared, elastically scalable and virtually hosted servers are made available to users anywhere there is an internet connection. Numerous companies provide cloud services online to meet the needs of various clientele. Since most cloud users lack their own computing capabilities, they must save their data, documents, and applications in the cloud in order to perform their work efficiently. the focus of this work is on the worldwide identification procedure utilising a digital passport in the cloud. there has been and will continue to be significant growth in cloud-based innovation and advancement in the coming years. Users can benefit greatly from cloud computing by delegating complex activities to remote data centers. Whether or not consumers can access the cloud's services is determined by the terms of the Service Level Agreement (SLA) in place between the cloud's suppliers and the users. By detecting when a service level agreement (SLA) has been broken, cloud service providers may boost customer confidence, decrease the likelihood of incurring costly fines, and boost their bottom line. this study makes two significant contributions to the fields of service provider selection for virtual machine (VM) migrations and SLA (service level agreement) violation detection in public cloud computing. the pros and cons of a passport-free international travel system were examined. this study has compared various research methodologies and frameworks for implementing new technologies. the present study is predicated on a Cloud Passport adoption model that was developed for previous work. © 2023 IEEE.

关键词： distributed database systems

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AI-Driven Symptom Checker: Leveraging Big Data technologies for Real-Time Healthcare Triage and Diagnostics 5

AI-Driven Symptom Checker: Leveraging Big Data Technologies ...

引用

5th international conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Banerjee, Augnik Baibhav, Piyush Kumar, Nitin Singh, Aniket Gouthaman, P. School of Computing College of Engineering and Technology SRM Institute of Science and Technology Department of Networking and Communications Kattankulathur603203 India School of Computing SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Networking and Communications Kattankulathur603203 India

ISBN: (纸本)9798331530013

the healthcare industry continues to face significant challenges in delivering timely and accurate diagnoses, particularly in remote and underserved areas where access to medical professionals is limited. the work aims to develop an AI-driven symptom checker that leverages big data technologies to offer preliminary diagnoses and support patient triage, ensuring quicker medical response times. Utilizing Hadoop for scalable data storage, Hive for advanced data analysis, and Spark for real-time distributed data processing, the system is designed to efficiently handle large volumes of patient data. Tableau is integrated for intuitive data visualization, allowing healthcare professionals to gain actionable insights and make informed decisions promptly. the proposed architecture enables the swift analysis of patient symptoms in real-time, significantly reducing diagnostic delays and enhancing the quality of care. By focusing on scalable and efficient data processing, the work addresses the need for a robust healthcare solution capable of operating in environments with limited resources. this system has the potential to transform patient care in remote areas by providing real-time analysis, identifying critical cases, and aiding in effective resource allocation. the solution's emphasis on rapid diagnosis and visualization offers a comprehensive approach to improving healthcare outcomes in underserved regions. © 2024 IEEE.

关键词： AI-Driven Symptom Checker Apache Spark Hadoop Healthcare Triage Hive Tableau

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Real-Time Information Collection and Scheduling Control in the Distribution Station Area with distributed New Energy 5

Real-Time Information Collection and Scheduling Control in t...

引用

5th international conference on Smart Power and internet Energy Systems, SPIES 2023

作者： Guanghui, Hua Yuchen, Hao Jianjun, Zhu Haixuan, Liu Chun, Wang Xiaohui, Xu China Electric Power Research Institute Jiangsu Province Nanjing China State Grid Jiangsu Electric Power Co. Ltd. Jiangsu Province Nanjing China

ISBN: (纸本)9798350371741

the low-voltage distribution network is facing a situation of blowout, small capacity and decentralized distributed new energy access, with the emergence of large-scale power reverse transmission and frequent voltage fluctuations at station area level. However, power grid companies find it difficult to timely perceive real-time information of electricity generation and consumption within the station area, witch increasing the difficulty of operation control and management of the distribution network, and bringing adverse effects to safe, stable and economic power supply. Following the idea of edge computing, a real-time information acquisition and dispatching control method suitable for distribution station area with distributed new energy is proposed to realize the information interconnection and integration of local equipment at a lower cost, so that various adjustable resources can participate in the multi-level source network load interaction operation, and improve the comprehensive benefits of the distribution system in the station area. © 2023 IEEE.

关键词： Electric power distribution

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A Reputation System for distributed Intelligent Blockchain Decision-Making 5

A Reputation System for Distributed Intelligent Blockchain D...

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5th international conference on Blockchain computing and Applications, BCCA 2023

作者： Rawlins, Charles Jagannathan, S. Nadendla, Venkata Sriram Siddhardh Electrical and Computer Engineering Missouri University of Science and Technology RollaMO United States Computer Science Missouri University of Science and Technology RollaMO United States

ISBN: (纸本)9798350339239

Discerning ground-truth amidst misinformation is a nontrivial task in decentralized networks. While trivial for traditional blockchain networks using Proof of Work (PoW) consensus, it requires immense computational resources at the cost of network scalability and therefore has compatibility challenges with limited devices like internet of things (IoT) networks. Moving towards a lightweight alternative-a novel scheme is proposed for provable identification of reputable nodes for making intelligent decisions using distributed machine-learning optimization, called Weight-Based Reputation (WBR). A distributed learning task identifies nodes that are willing to cooperate as a means for securing ground-truth, and is provably resistant to data poisoning in theory and experimentation. A novel method combining WBR with a classifier creates lightweight and robust blockchain decision-making. the results of this two-step approach is a novel method for predicting various attacks that result transaction log, such as fraud or the double-spend. A Bayesian game against adversary manipulation formulation and experimental results show superior performance and robustness to the state-of-the-art. Resource consumption compared against blockchain protocols is also provided. Future work will explore WBR in distributed consensus as a complete alternative to blockchain PoW. © 2023 IEEE.

关键词： internet of things

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Dual Timescale Orchestration System for Elastic Control of NextG Cloud-Integrated Networks 27

Dual Timescale Orchestration System for Elastic Control of N...

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27th conference on Innovation in Clouds, internet and Networks (ICIN)

作者： Pagliuca, Quirino Chaves, Luciano Jerez Imputato, Pasquale Tulino, Antonia Llorca, Jaime Univ Naples Federico II Naples Italy Univ Fed Juiz de Fora Juiz De Fora Brazil NYU New York NY USA

ISBN: (纸本)9798350393767;9798350393774

the confluence of advanced networking (5G/6G) and distributed cloud technologies (edge/fog computing) are rapidly transforming next-generation networks into highly distributed computation platforms, especially suited to host emerging resource-intensive and latency-sensitive services (e.g., smart transportation/city/factory, real-time computer vision, augmented reality). In this paper, we leverage the recently proposed Cloud Network Flow (CNF) modeling and optimization framework to design a novel two-timescale orchestration system for the joint control of communication and computation resources in cloud-integrated networks. the Long-Term Controller solves a properly constructed CNF optimization problem at a longer timescale that determines i) the end-to-end CNF routes (defining data paths and processing locations) for each service chain and ii) the associated allocation of communication and computation resources. the Short-Term Controller uses a local control policy to adjust the allocation of communication and computation resources based on queue state observations at a shorter timescale. Driven by the lack of proper simulation tools, we also develop new ns-3 features that allow modeling and simulation of cloud-integrated networks equipped with both communication and computation resources hosting arbitrary service chains. Finally, we integrate the proposed orchestration system into ns-3 to evaluate and analyze the dynamic orchestration of a set of representative service chains over a hierarchical cloud-integrated network.

关键词： 5G 6G cloud networks edge computing service orchestration network modeling network simulation ns-3

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Real-Time Adaptive Intrusion Detection System [RTPIDS] for internet of things Using Federated Learning and Blockchain 5

Real-Time Adaptive Intrusion Detection System [RTPIDS] for I...

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5th international conference on Data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Sunil Raj, Y. Parimala, E. Helen Bosco, V. S. Jayakumar Paul Adarsh Samuel Raj, J. Kumar, P.J. Rosario Vasantha Kolluru, Vinothkumar Department of Data Science Palayamkottai627 002 India Gitam Deemed to be University Department of Computer Science Bangalore India Department of Bca Tirupattur635601 India San Jose State University San JoseCA United States Palayamkottai627002 India Stevens Institute of Technology Department of Data Science 1 Castle Point Terrace HobokenNJ07030 United States

ISBN: (纸本)9798350389609

In the growing field of the internet of things (IoT), ensuring security and privacy has become a critical concern, particularly in sensitive domains such as healthcare. this paper presents a Real-Time Adaptive Intrusion Detection System (IDS) specifically designed for internet of Medical things (IoMT) networks. the proposed system leverages Federated Learning (FL) and Blockchain technologies to address key challenges, including handling non-independent and identically distributed (non-IID) data, ensuring secure model updates, and providing real-time detection capabilities. By employing FL, the system enables IoMT devices to collaboratively train models without sharing sensitive data, thereby preserving privacy and improving scalability. Blockchain integration further enhances the system by ensuring the integrity and security of model updates, mitigating risks of tampering. the system demonstrates strong performance in detecting simpler intrusions in real-time, though additional enhancements are required to manage more complex attacks and large-scale IoT deployments. this work contributes a robust and scalable IDS framework, particularly valuable for protecting critical IoT environments such as healthcare networks. © 2024 IEEE.

关键词： Federated learning

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An Empirical Assessment of Botnets and Detection Methods 15

An Empirical Assessment of Botnets and Detection Methods

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15th international conference on Advances in computing, Control, and Telecommunication technologies, ACT 2024

作者： Shivanna, D. Pooja, M.R. Department of Computer Science and Engineering Vidyavardhaka College of Engineering Mysuru India

ISBN: (纸本)9798331300579

a botnet is a group of devices which are controlled by the Attacker and used for fraud, scam and *** attacker is also known as *** Bots are used to conduct many activities varies from stealing user credentials, sending spam, stealing data, ransom ware, fraudulently clicking on ads or distributed denial-of-service (DDoS) *** traffic made up by bots is increasing day by day, now nearly a quarter of the whole *** them becomes an uphill task as the time *** developers are adopting new technologies at a rapid rate in an effort to avoid bot *** some bot problems are industry-specific, researchers found out that bot problems run across all *** top five industries which are targeted with bad bot traffic are the financial, education, IT & services industries, marketplaces, and *** assessment paper briefs the different botnet detection methods that exist at *** main aim of this paper is to give the insight knowledge of various bots and their implications on the present cyber world and also shedding some light on the current methods using to detect them... © Grenze Scientific Society, 2024.

关键词： Bot (internet)

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A Review of Cyber Security Challenges and Mitigation Strategies in Industry 4.0 technologies 5

A Review of Cyber Security Challenges and Mitigation Strateg...

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5th IEEE international conference on Advances in computing, Communication Control and Networking, ICAC3N 2023

作者： Kumar, Mayank Gupta, Himanshu Aiit Amity University Noida India

ISBN: (纸本)9798350330861

the 4th Industrial Revolution, also known as or the Industry 4.0, has been characterized by the emergence of revolutionary technologies like robotics, computer vision, big data the analysis, and the internet of things, or IoT for short, directly into the operations of industries. As these technologies become increasingly widespread, they also introduce new cybersecurity risks that need to be addressed. this paper provides a comprehensive review of the current literature on cyber security challenges and mitigation strategies in Industry 4.0. the research approach involved a systematic literature review of academic journals, conference proceedings, and relevant reports and studies. the review's findings emphasize the most significant cyber security concerns impacting the Industry 4.0 movement, including data privacy and security, network security, and system integrity. the paper also identifies and evaluates the strategies used to mitigate these challenges, including encryption, access control, and network segmentation. the analysis section interprets the findings, draws meaningful conclusions and offers valuable recommendations for future research and practical applications. the research paper delivers an input to the topic of cyber security within Industry 4.0 by offering an in-depth review regarding the domain's present circumstances and presenting prospective directions for additional research and advancement. © 2023 IEEE.

关键词： Cryptography

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