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Federated Learning on Internet of Things:Extensive and Systematic Review

Computers, Materials & Continua 2024年第5期79卷 1795-1834页

作者： Meenakshi Aggarwal Vikas Khullar Sunita Rani Thomas AndréProla Shyama Barna Bhattacharjee Sarowar Morshed Shawon Nitin Goyal Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Department of CSE&IT BPS Mahila VishwavidyalayaKhanpur KalanSonipatHaryana131305India Engineering Research&Innovation Group Universidad Europea del AtlánticoC/Isabel Torres 21Santander39011Spain Department of Project Management Universidad Internacional IberoamericanaAreciboPR00613USA Department of Project Management Universidade Internacional do CuanzaEstrada Nacional 250Bairro KaluapandaCuito-BiéAngola Department of Computer Science and Engineering University of Science and Technology Chittagong(USTC)Chattogram4202Bangladesh Deptartment of EEE University of Science and Technology Chittagong(USTC)Chattogram4202Bangladesh Department of Computer Science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendragarhHaryana123031India

The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data ***,fl development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world *** paper systematically reviewed the available literature using the PRISMA guiding *** study aims to provide a detailed overview of the increasing use of fl in IoT networks,including the architecture and challenges.A systematic review approach is used to collect,categorize and analyze fl-IoT-based *** was performed in the IEEE,Elsevier,Arxiv,ACM,and WOS databases and 92 articles were finally *** measures were published in English and with the keywords“fl”and“IoT”.The methodology begins with an overview of recent advances in fl and the IoT,followed by a discussion of how these two technologies can be *** be more specific,we examine and evaluate the capabilities of fl by talking about communication protocols,frameworks and *** then present a comprehensive analysis of the use of fl in a number of key IoT applications,including smart healthcare,smart transportation,smart cities,smart industry,smart finance,and smart *** key findings from this analysis of fl IoT services and applications are also ***,we performed a comparative analysis with fl IID(independent and identical data)and non-ID,traditional centralized deep learning(DL)*** concluded that fl has better performance,especially in terms of privacy protection and resource *** is excellent for preserving privacy becausemodel training takes place on individual devices or edge nodes,eliminating the need for centralized data aggregation,which poses significant privacy *** facilitate development in this rapidly evolving field,the insights presented are intended to help practitioners and re

关键词： Internet of Things federated learning PRISMA framework of fl applications of fl data privacy communication

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