This paper investigates a multi-node wireless powered communication network (WPCN),
where a hybrid access point (HAP) first charges an Internet of Thing (IoT) device wirelessly …

Federated learning (FL) is a type of distributed machine learning approacs that trains global
models through the collaboration of participants. It protects data privacy as participants only …

Edge computing brings computing and storage resources closer to (mobile) end users and
data sources, thus bypassing expensive and slow links to distant cloud computing …

Computing tasks offloaded from user devices (UDs) can be carried out by one or more
mobile edge computing (MEC) servers to alleviate the computing burden of UDs. The …

The fog paradigm extends the cloud capabilities at the edge of the network. Fog computing-
based real-time applications (Online gaming, 5G, Healthcare 4.0, Industrial IoT, autonomous …

Abstract Mobile Edge Computing (MEC) enables smart mobile devices to handle
computationally intensive tasks with limited resources. By offloading tasks to the edge of the …

Abstract Mobile Edge Computing is a new computing paradigm that offers cloud
computation capabilities at the edge of the mobile network. Due to the proximity to Mobile …

We study the intelligent offloading problem for a multiple unmanned aerial vehicle (multi-
UAV)-assisted mobile-edge computing (MEC) system in an MEC scenario where a natural …

The huge amount of data generated by the Internet of things (IoT) devices needs the
computational power and storage capacity provided by cloud, edge, and fog computing …

Due to the growing demand for delay-sensitive applications, partial offloading is very
important in fog/cloud computing. In partial offloading, different parts of each task are run in …