For an effective, low latency, and ultra reliable pervasive connectivity among next-
generation wireless networks such as Internet of Things (IoT) devices, machine-to-machine …

Federated learning (FL) can enable distributed model training over mobile nodes without
sharing privacy-sensitive raw data. However, to achieve efficient FL, one significant …

Today massive amounts of data are generated from Internet-of-Things (IoT) sensors that can
be streamed in real-time and utilized for building valuable services. As the demand for data …

With the volume of data increasing in the Internet of Things, a new business mode, where
data owners share their own data to others for rewards, has emerged. Therefore, how to …

Federated learning (FL) enables collaborative model training over distributed computing
nodes without sharing their privacy-sensitive raw data. However, in FL, iterative exchanges …

As the number of smart cars grows rapidly, vehicular crowdsensing (VCS) is gradually
becoming popular. In a VCS infrastructure, sensing devices and computing units hold on …

With the development of 5G/6G communication networks, the industrial Internet of Things
(IIoT) industry has generated a massive amount of data, presenting opportunities for …

Data is the new oil of the 21st century. The growing trend of trading data for greater welfare
has led to the emergence of data markets. A data market is any mechanism whereby the …

Edge computing (EC) enables low-latency services by pushing computing resources to the
network edge. Due to the geographic distribution and limited capacities of edge servers, EC …

The explosive growth of Internet of things (IoT) devices has promoted the prosperity of virtual
reality applications, which can be realized by service offloading with the assistance of …