As the number of IoT devices and the volume of data increase, distributed computing systems have become the primary deployment solution for large-scale Internet of Things (IoT) environments. Federated learning (FL) is...
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ISBN:
(纸本)9783031751097;9783031751103
As the number of IoT devices and the volume of data increase, distributed computing systems have become the primary deployment solution for large-scale Internet of Things (IoT) environments. Federated learning (FL) is a collaborative machine learning framework that allows for model training using data from all participants while protecting their privacy. However, traditional FL suffers from low computational and communication efficiency in large-scale hierarchical cloud-edge collaborative IoT systems. Additionally, due to heterogeneity issues, not all IoT devices necessarily benefit from the global model of traditional FL, but instead require the maintenance of personalized levels in the global training process. Therefore we extend FL into a horizontal peer-to-peer (P2P) structure and introduce our P2PFL framework: Efficient Peer-to-peer Federated learning for Users (EPFLU). EPFLU transitions the paradigms from vertical FL to horizontal P2P structure from the user perspective and incorporates personalized enhancement techniques using private information. Through horizontal consensus information aggregation and private information supplementation, EPFLU solves the weakness of traditional FL that dilutes the characteristics of individual client data and leads to model deviation. This structural transformation also significantly alleviates the original communication issues. Additionally, EPFLU has a customized simulation evaluation framework to make it more suitable for real-world large-scale IoT. Within this framework, we design extreme data distribution scenarios and conduct detailed experiments of EPFLU and selected baselines on the MNIST and CIFAR-10 datasets. The results demonstrate that the robust and adaptive EPFLU framework can consistently converge to optimal performance even under extreme data distribution scenarios. Compared with the selected vertical aggregation and horizontal transmission cumulative aggregation methods, EPFLU achieves communication improve
Supply Chain Management is a quintessential task of every firm as it is the core of the business. A business is driven entirely by customer behaviour, change in seasonal demand and how the customer expand or shrunk th...
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This research focuses on the implementation of quantum machine learning with the classical models such as Gradient Boosting and K-means clustering for efficient classification and clustering of most complex datasets i...
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Hybrid teaching become a major part of the teaching style for the higher education sector in the Sri Lankan context. Hybrid teaching allows for a part of the academics to go to the course physically and simultaneously...
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With the rapid augmentation of the Internet and communication technology, interest in online learning continues to rapidly broaden the horizons of academic institutions. One of the most important components of the e-l...
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Within the dynamic field of planetary defence, machine learning has emerged as a key component that is essential to early warning systems that are tasked with forecasting the orbits and trajectories of potentially dan...
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The proceedings contain 15 papers. The special focus in this conference is on Emerging Technologies in computing. The topics include: On the Design and Performance Evaluation of Android Based Alarming Applications;inv...
ISBN:
(纸本)9783031502149
The proceedings contain 15 papers. The special focus in this conference is on Emerging Technologies in computing. The topics include: On the Design and Performance Evaluation of Android Based Alarming Applications;investigation of Air Effluence Using IoT and Machine learning;exploring the Emerging Technologies Within the Blockchain Landscape;socialEcho: A Social Networking Platform with Community Guidelines Violation Pre-check;green-IoT Based Automated Field Maintenance System;chaotic Chimp Based African Vulture Optimization Algorithm with Stability Tests for Feature Selection Algorithms;event-Based Data Pipelines in Recommender Systems: The Data engineering Perspective;pre-planning for Plastic Surgery Using Machine learning: A Proof of Concept;academic Integrity in the Face of Generative Language Models;docBot: A System for Disease Detection and Specialized Doctor Recommendation Using Patient’s Speech of Symptoms;Digitalisation Transformation in High Schools: Analysis of the COVID-19 Pandemic’s Accelerating Impact;Cube Attacks on Round-Reduced Grain-128AEAD;a Literature Review of Various Analysis Methods and Classification techniques of Malware.
In the last few years, there has been remarkable progress in the domain of natural language generation & understanding. This has led to the development of enhanced text generation capability of machines that can g...
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In mobile edge computing (MEC) systems, unmanned aerial vehicles (UAVs) have garnered significant research and application attention due to their high flexibility and ease of deployment. However, given the limited ene...
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The Internet of Things (IoT) is a rapidly established technology that combines various domains and such technology permits devices to process, transfer, and receive information without the involvement of humans. Howev...
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