Mobile-edge computing (MEC) has been envisioned as a promising paradigm to handle the
massive volume of data generated from ubiquitous mobile devices for enabling intelligent …

Federated learning is a privacy-preserving machine learning technique that trains models
across multiple devices holding local data samples without exchanging them. There are …

Federated learning is promising in enabling large-scale machine learning by massive
clients without exposing their raw data. It can not only enable the clients to preserve the …

Recent advancements in the Internet of Health Things (IoHT) have ushered in the wide
adoption of IoT devices in our daily health management. For IoHT data to be acceptable by …

As an important technology to ensure data security, consistency, traceability, etc., blockchain
has been increasingly used in Internet of Things (IoT) applications. The integration of …

The Internet of Things (IoT) aims to enable a scenario where smart objects, inserted into
information networks, supply smart services for human beings. The introduction of edge …

Given the explosive growth of portable devices, mobile crowdsensing (MCS) is becoming an
essential approach that fully utilizes pervasive idle resources to accomplish sensing tasks …

The air-ground network provides users with seamless connections and real-time services,
while its resource constraint triggers a paradigm shift from machine learning to federated …

Edge networking is a complex and dynamic computing paradigm that aims to push cloud re-
sources closer to the end user improving responsiveness and reducing backhaul traffic …

Advances in communications and networking technologies are driving the computing
paradigm toward the end-edge-cloud collaborative architecture to leverage ubiquitous data …