Limitations and future aspects of communication costs in federated learning: A survey
M Asad, S Shaukat, D Hu, Z Wang, E Javanmardi… - Sensors, 2023 - mdpi.com
This paper explores the potential for communication-efficient federated learning (FL) in
modern distributed systems. FL is an emerging distributed machine learning technique that …
modern distributed systems. FL is an emerging distributed machine learning technique that …
Boosted federated learning based on improved Particle Swarm Optimization for healthcare IoT devices
EH Houssein, A Sayed - Computers in Biology and Medicine, 2023 - Elsevier
As healthcare data becomes increasingly available from various sources, including clinical
institutions, patients, insurance companies, and pharmaceutical industries, machine …
institutions, patients, insurance companies, and pharmaceutical industries, machine …
DRL-Based Backbone SDN Control Methods in UAV-Assisted Networks for Computational Resource Efficiency
The limited coverage extension of mobile edge computing (MEC) necessitates exploring
cooperation with unmanned aerial vehicles (UAV) to leverage advanced features for future …
cooperation with unmanned aerial vehicles (UAV) to leverage advanced features for future …
A hybrid model for energy-efficient Green Internet of Things enabled intelligent transportation systems using federated learning
In the rapidly evolving Internet of Things domain, managing voluminous data streams while
ensuring energy efficiency remains a cardinal challenge. Our research introduces a hybrid …
ensuring energy efficiency remains a cardinal challenge. Our research introduces a hybrid …
A novel deep hierarchical machine learning approach for identification of known and unknown multiple security attacks in a d2d communications network
Intrusion Detection Systems (IDSs) have played a crucial role in identifying cyber threats for
a very long time. Still, their significance has increased significantly with the advent of 5G/6G …
a very long time. Still, their significance has increased significantly with the advent of 5G/6G …
Hybrid modeling for stream flow estimation: integrating machine learning and federated learning
In the face of mounting global challenges stemming from population growth and climate
fluctuations, the sustainable management of water resources emerges as a paramount …
fluctuations, the sustainable management of water resources emerges as a paramount …
Blockchain-Enabled Federated Reinforcement Learning (B-FRL) model for privacy preservation service in IoT systems
The rapid explosion of Internet of Things (IoT) devices has resulted in extraordinary data
generation, necessitating advanced methods for data processing and privacy preservation …
generation, necessitating advanced methods for data processing and privacy preservation …
A Data Analytic Monitoring with IoT System of the Reproductive Conditions of the Red Worm as a Product Diversification Strategy
KY Sánchez-Mojica, LA Pérez-Domínguez… - Applied Sciences, 2023 - mdpi.com
The Internet of Things (IoT) is becoming increasingly important due to the ability to collect
data in real time and monitor the performance of systems. In this sense, the objective of the …
data in real time and monitor the performance of systems. In this sense, the objective of the …
Addressing security challenges in industry 4.0: AVA-MA approach for strengthening SDN-IoT network security
RU Mageswari, GA MM - Computers & Security, 2024 - Elsevier
In the context of Industry 4.0, the convergence of the Internet of Things (IoT) and Software
Defined Networking (SDN) represents a challenging yet pivotal avenue for bolstering …
Defined Networking (SDN) represents a challenging yet pivotal avenue for bolstering …
Offloading Decision and Resource Allocation in Mobile Edge Computing for Cost and Latency Efficiencies in Real-Time IoT
Internet of Things (IoT) devices can integrate with applications requiring intensive contextual
data processing, intelligent vehicle control, healthcare remote sensing, VR, data mining …
data processing, intelligent vehicle control, healthcare remote sensing, VR, data mining …