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Emerging Trends and Future Prospects in internet of things (IoT) Technology 5

Emerging Trends and Future Prospects in Internet of Things (...

引用

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

作者： Sathya, U. Hashini, S. Lakshmipriya, C. Varun, C.M. Nalini, M. Siva Subramanian, R. Saveetha Engineering College Dept of CSE Chennai602105 India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India S A Engineering College Dept of CSE India R.M.K. Engineering College Dept of CSBS India R.M.K College of Engg and Tech Dept of CSE India

ISBN: (纸本)9798331530013

the internet of things (IoT) can be described as an innovative approach and a new perspective towards the world and things existing in it. the present survey paper offers details on the definition of IoT, the constituents of its architecture, the technologies that facilitate IoT, key security concerns, IoT applications in different fields, social implications of IoT, and potential developments in the future of IoT. the architecture of IoT is divided into layers based on devices, communication, software, and applications which stipulates the interconnection of IoT systems. the enabling technologies like wireless communication systems or standards, embedded systems, and cloud computing are explained in detail with specific examples of their usefulness in IoT implementation. Security and privacy become two significant issues in the IoT context, raising the debate about issues, current solutions, and potential approaches. these use cases in smart cities, healthcare, and industries confirm that IoT has the potential to revolutionize operations through increased efficiency, sustainability, and improved quality of life. In addition, this paper also examines the social and economic impact of IoT, presents the recent trends like AI, recommendation, and regulations. Based on the assumptions of the present and possible future development of IoT, this survey seeks to establish the primitives for the development of IoT in orientation, obstacles, and possibilities for the formation of the digital age. © 2024 IEEE.

关键词： Cloud security

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Service Function Chain Resource Allocation and Offloading in Constrained Edge-Cloud Optical Networks 24

Service Function Chain Resource Allocation and Offloading in...

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24th international conference on Transparent Optical Networks (ICTON)

作者： Asdiluan, Jean Pierre Gjeka, Daniele Pages, Albert Troia, Sebastian Maier, Guido Spadaro, Salvatore Politecn Milan Dept Elect Informat & Bioengn Milan Italy Univ Politecn Cataluna Adv Broadband Commun Ctr Barcelona Spain

ISBN: (纸本)9798350377330;9798350377323

internet Service Providers (ISPs) face escalating data traffic and diverse application needs, prompting the adoption of 5G technology to enhance network agility and intelligence. However, traditional networks fall short, necessitating the integration of Network Function Virtualization (NFV), Software-Defined Networking (SDN), and Multi-access Edge computing (MEC). Despite advancements, efficient resource allocation remains a challenge, especially with edge computing. this study evaluates Mixed Integer Linear Programming (MILP) and Heuristic algorithms for Virtual Network Embedding (VNE) in 5G networks. Results provide insights into optimal resource allocation and offloading strategies.

关键词： 5G NFV VNF Edge computing SFC SDN

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Applying Machine Learning to Enhance Human Resource Management Strategies for Improved Organisational Results 2

Applying Machine Learning to Enhance Human Resource Manageme...

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2nd IEEE international conference on Trends in Quantum computing and Emerging Business technologies, TQCEBT 2024

作者： Joshi, Meeta Misal, Ashutosh N Gosavi, Pranita R Gautam, Sharad Lourens, Melanie Mungekar, Pratik Rajan Marwadi University Faculty of Management Studies India Indira Institute of Management Pune India Waltham International College London United Kingdom Graphic Era Hill University School of Management Haldwani Campus India Durban University of Technology Faculty of Management Sciences South Africa London United Kingdom

ISBN: (纸本)9798350384277

Organizations can undoubtedly count on technologies to continue to have an important part in human resource management in the period of the 5th industrial transformation. this transformation is being made possible by a number of innovations, including robotics, internet of things (IOT), cloud services, big data, and artificial intelligence, or AI. the retention rate is rather high in staff members that fall into such group since only contented workers are productive workers. Finding the elements that contribute worker happiness will undoubtedly assist management include workable elements within the ones that are already discovered. this is the application of machine learning. Efficient prediction-making and data analysis depend heavily on machine learning methods such as grouping and segmentation. In an effort to reduce worker turnover, this article attempts to explore how machine learning affects human resource management. © 2024 IEEE.

关键词： Adversarial machine learning

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5th international conference on Advances in distributed computing and Machine Learning, ICADCML 2024

5th International Conference on Advances in Distributed Comp...

引用

5th international conference on Advances in distributed computing and Machine Learning, ICADCML 2024

ISBN: (纸本)9789819718405

the proceedings contain 35 papers. the special focus in this conference is on Advances in distributed computing and Machine Learning. the topics include: Computer-Aided Bundle Branch Block Detection Using Symbolic Features of ECG Signal;block-Chain and Cloud-Based Tender Allocation System;reliability Assessment of IoT-Enabled Systems Using Fault Trees and Bayesian Networks;resnet-50 Integrated with Attention Mechanism for Remote Sensing Classification;revolutionizing Data Annotation with Convergence of Deep Learning and Active Learning to Enhance Credibility on Twitter Datasets;statistical and Deep-Learning Approaches for Individual Carbon Footprint Calculation in India;intelligent Healthcare System Using Emerging technologies: A Comprehensive Survey;Efficient Energy Management by Using SJF Scheduling in Wireless Sensor Network;cost Effective and Energy Efficient Drip Irrigation System for IoT Enabled Smart Agriculture;facial Detection and Recognition in Drone Imagery Using FaceNet;valluvan: Processing Name Board Images to Enhance Communication for Native Tamil Speakers;Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud computing;A Study on the Mental Health Among Indian Population in the Post COVID-19 Pandemic Using Computational Intelligence;Cloud-Based Anomaly Detection for Broken Rail Track Using LSTM Autoencoders and Cross-modal Audio Analysis;Face Recognition Using CNN for Monitoring and Surveillance of Neurological Disorder Patients;a Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-colour Space Feature Fusion and Quantum–Classical Stack Ensemble Method;comparative Analysis of Deep Learning-Based Hybrid Algorithms for Liver Disease Prediction;preface;performance Improvements of Covert Timing Channel Detection in the Era of Artificial Intelligence;sign Detection Using an N-Gram Language Model and MobileNet.

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5th international conference on Advances in distributed computing and Machine Learning, ICADCML 2024

5th International Conference on Advances in Distributed Comp...

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5th international conference on Advances in distributed computing and Machine Learning, ICADCML 2024

ISBN: (纸本)9789819735228

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A Mathematical Model for Data Traffic Management in Next-Generation IoT Networks 5th

A Mathematical Model for Data Traffic Management in Next-G...

引用

5th international conference on computing and Network Communications, CoCoNet 2023

作者： George, Gemini Department of Computer Applications St. George’s College Aruvithura Erattupetta Kerala Kottayam686122 India

ISBN: (纸本)9789819745395

the rapid deployment of IoT networks in different industrial services has caused the emanation of a huge volume of data from sensors and monitors. the efficient analysis and compact representation of the big data generated is critical to managing its transfer, storage, and latency. In this work, we propose a novel graphical model that has the flexibility to adapt to different architectural features of distributed IoT systems with low-power sensors. Further, we consider the traffic load minimization problem in the network and map the problems of network coverage and clustering onto the graph to find an optimal distributed network structure that minimizes the traffic load. the proposed approaches are tested under different network conditions, and the simulation results emphasize the improved performance of the method. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： internet of things

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LLRS : A Low latency Resource Scheduling in Cloud Continuum orchestration 27

LLRS : A Low latency Resource Scheduling in Cloud Continuum ...

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

作者： Mukuhi, David Kule Outtagarts, Abdelkader Nokia Networks France Bell Labs Massy France Univ Gustave Eiffel Champs Sur Marne France

ISBN: (纸本)9798350393767;9798350393774

the convergence of Network Function Virtualization (NFV) and Cloud computing marks a transformative milestone in the telecommunications domain, setting the stage for the realization of 5G/6G flagship technologies. Containers, as a rising virtualization solution, have gained significant traction in recent years due to their attributes like shared host OS, swift launch times, and portability. A central challenge in this landscape is the effective orchestration of resources within cloud continuum infrastructure, ensuring seamless service operation. the abstraction of network services through NFV and the concept of network slicing amplify challenges in resource allocation. Kubernetes and Docker Swarm have emerged as powerful orchestration platforms. However, while widely adopted in application deployment, these solutions must meet the distinctive quality-of-service (QoS) demands of the telecommunications industry like Ultra-reliable low-latency communication. this paper proposes a Low Latency Resource Scheduler (LLRS) for Cloud Continuum. this new scheduling architecture approach leverages in-memory data grid and distributed resource predictions to reduce scheduling delay. Our experiments on heterogeneous environment has shown a reduction of nearly half the time required to schedule container in docker swarm and Kubernetes.

关键词： distributed Orchestration In-memory database low latency scheduling machine learning

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Designing distributed Deep Learning Architectures for 5G Network Slicing 15

Designing Distributed Deep Learning Architectures for 5G Net...

引用

15th international conference on computing Communication and Networking technologies, ICCCNT 2024

作者： Kumari, Sweta Shree, Ritu Kumar, R. thanga Department of Law ARKA JAIN University Jharkhand Jamshedpur India Department of Computer Science & Application Vivekananda Global University Jaipur India Karnataka Bangalore India

ISBN: (纸本)9798350370249

the intention present day this paper is to advise a dispensed deep ultra-modern (DL) architecture for 5G network slicing. the proposed allotted DL structure utilizes distributed nodes to learn about the network slices. the dispensed nodes and the community slices are interconnected via an orchestrator, for this reason, supplying a comprehensive view present day the environment. Furthermore, the distributed DL structure leverages switch mastering to enhance its overall performance in dispensed situations. In addition, it is also an aspect computing node to research visitors' styles present day the 5G slices. Eventually, the proposed allotted DL architecture has been aligned with the 5G architecture, and the disbursed nodes are related through a 5G cellular community. the experimental consequences demonstrate that the proposed allotted DL architecture provides performance for network cutting while lowering the strength consumption and improving community security. ©2024 IEEE.

关键词： 5G mobile communication systems

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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...

引用

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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