Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey
With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous
networks, mobile broadband users are generating massive volumes of data that undergo …
networks, mobile broadband users are generating massive volumes of data that undergo …
Anti-Byzantine attacks enabled vehicle selection for asynchronous federated learning in vehicular edge computing
In vehicle edge computing (VEC), asynchronous federated learning (AFL) is used, where the
edge receives a local model and updates the global model, effectively reducing the global …
edge receives a local model and updates the global model, effectively reducing the global …
Communication optimization techniques in Personalized Federated Learning: Applications, challenges and future directions
Abstract Personalized Federated Learning (PFL) aims to train machine learning models on
decentralized, heterogeneous data while preserving user privacy. This research survey …
decentralized, heterogeneous data while preserving user privacy. This research survey …
Joint self-organizing maps and knowledge distillation-based communication-efficient federated learning for resource-constrained UAV-IoT systems
The adoption of Internet of Things (IoT) and monitoring devices in 5G and beyond networks
has been widespread. Unmanned aerial vehicles (UAVs) have shown success in …
has been widespread. Unmanned aerial vehicles (UAVs) have shown success in …
Rf energy harvesting effectiveness in relay-based d2d communication
The energy harvesting (EH) of radio frequency (RF) has taken attention to solve the wireless
devices' energy problem. On the other hand, relays play a crucial role in improving device-to …
devices' energy problem. On the other hand, relays play a crucial role in improving device-to …
Communication-efficient federated learning in drone-assisted IoT networks: Path planning and enhanced knowledge distillation techniques
As 5G and beyond networks continue to proliferate, intelligent monitoring systems are
becoming increasingly prevalent. However, geographically isolated regions with sparse …
becoming increasingly prevalent. However, geographically isolated regions with sparse …
Federated Learning Algorithm Handling Missing Attributes
Federated learning has gained considerable attention as the solution for handling
distributed and privacy-sensitive data. This includes scenarios such as predicting …
distributed and privacy-sensitive data. This includes scenarios such as predicting …
PC-SSL: Peer-Coordinated Sequential Split Learning for Intelligent Traffic Analysis in mmWave 5G Networks
Fifth Generation (5G) networks operating on mmWave frequency bands are anticipated to
provide an ultrahigh capacity with low latency to serve mobile users requiring high-end …
provide an ultrahigh capacity with low latency to serve mobile users requiring high-end …
Federated learning framework for prediction based load distribution in 5G network slicing
N Dutta, SP Patole, R Mahadeva… - Proceedings of the 2024 …, 2024 - dl.acm.org
The 5G technology brings transformative changes across sectors like healthcare,
automotive, and entertainment by integrating massive IoT networks and supporting dense …
automotive, and entertainment by integrating massive IoT networks and supporting dense …
Abnormal Network Traffic Detection Algorithm Based on Improved Convolutional Neural Network
L Chen, T Zhang, Y Ma, M Chen - … International Conference on …, 2024 - ieeexplore.ieee.org
With the increasing complexity, automation, and intelligence of network attacks, new types of
attacks are constantly emerging in the network, posing great challenges to network attack …
attacks are constantly emerging in the network, posing great challenges to network attack …