Data marketplaces are expected to play a crucial role in tomorrow's data economy, but such
marketplaces are seldom commercially viable. Currently, there is no clear understanding of …

Federated learning (FL) is a privacy-preserving distributed machine learning framework,
which involves training statistical models over a number of mobile users (ie, workers) while …

Data has been increasingly recognized as a critical factor in the future economy. However,
constructing an efficient data trading market faces challenges such as privacy breaches …

The rapid growth of renewable energy has increased the requirements of the smart grid for
communication and processing capabilities. As an effective solution to collect and manage …

Incentive mechanisms are essential for stimulating adequate worker participation to achieve
good truth discovery performance in mobile crowdsensing (MCS) systems. However, most of …

With the widespread of Internet-of-Things (IoT) environment, a big data concept has
emerged to handle a large number of data generated by IoT devices. Moreover, since data …

The development of low-carbon power systems has not only elevated the investment costs
of power enterprises, but also generated a vast amount of electricity data. The electricity data …

Next-generation wireless technology and machine-to-machine technology can provide the
ability to connect and share data at any time among IoT smart devices. However, the …

With the development of the Internet of Things (IoT), the number of mobile terminal devices
is increasing rapidly. Due to high transmission delay and bandwidth limitation, computing …

A large number of IoT devices geographically distributed in urban areas makes it attractive
to collect massive data in a crowdsourced manner. To fully exploit the value of …