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

With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless
networks, the surging demand for data communications and computing calls for the …

With the development of communication and networking technologies, the Internet of
Vehicles (IoV) has become the foundation of smart transportation. The development of …

Abstract The Internet of Things (IoT) allows communication between devices, things, and
any digital assets that send and receive data over a network without requiring interaction …

Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

To enable the large scale and efficient deployment of Artificial Intelligence (AI), the
confluence of AI and Edge Computing has given rise to Edge Intelligence, which leverages …

In recent years, the rapid urbanization of world's population causes many economic, social,
and environmental problems, which affect people's living conditions and quality of life …

Blockchain, as the underlying technology of crypto-currencies, has attracted significant
attention. It has been adopted in numerous applications, such as smart grid and Internet-of …

The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

By leveraging blockchain, this letter proposes a blockchained federated learning (BlockFL)
architecture where local learning model updates are exchanged and verified. This enables …