The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of Things (IoT), billions of …
J Li, Y Shao, K Wei, M Ding, C Ma, L Shi… - … on Parallel and …, 2021 - ieeexplore.ieee.org
Federated learning (FL), as a distributed machine learning paradigm, promotes personal privacy by local data processing at each client. However, relying on a centralized server for …
A Boualouache, T Engel - IEEE Communications Surveys & …, 2023 - ieeexplore.ieee.org
Advances in Vehicle-to-Everything (V2X) technology and onboard sensors have significantly accelerated deploying Connected and Automated Vehicles (CAVs). Integrating V2X with 5G …
In federated learning (FL), model training is distributed over clients and local models are aggregated by a central server. The performance of uploaded models in such situations can …
Massive developments in mobile wireless telecommunication networks have been made during the last few decades. At present, mobile users are getting familiar with the latest 5G …
Abstract Open Data Processing Services (ODPS) offers vast storage capacity and excellent efficiency, which collects and stores a lot of data. As an essential component of ODPS …
As smart devices and mobile positioning technologies improve, location-based services (LBS) have grown in popularity. The LBS environment provides considerable convenience …
Owing to the low communication costs and privacy-promoting capabilities, federated learning (FL) has become a promising tool for training effective machine learning models …
G Qiu, G Tang, C Li, D Guo, Y Shen… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Crowdsensing-based mobile Internet, while facilitating users' daily life, also raises privacy concerns because of sharing user location trajectories. Combining with open-source …