Since reinforcement learning algorithms are notoriously data-intensive, the task of sampling
observations from the environment is usually split across multiple agents. However …

Mobile edge computing (MEC) is a promising paradigm, which brings computation
resources in proximity to mobile devices and allows the tasks of mobile devices to be …

Authentication is the first entrance to kinds of information systems; however, traditional
centered single-side authentication is weak and fragile, which has security risk of single-side …

To fulfill people's expectations for smart and user-friendly Internet of Things (IoT)
applications, the quantity of processing is fast expanding, and task latency constraints are …

As an emerging technique, mobile-edge computing (MEC) introduces a new scheme for
various distributed communication-computing systems, such as industrial Internet of Things …

Profit maximization of electric vehicle charging station (EVCS) operation yields an
increasing investment for the deployment of EVCSs, thereby increasing the penetration of …

Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry 4.0 and
paves an insight for new industrial era. Nowadays smart machines and smart factories use …

Federated learning (FL) is an emerging technology for empowering various applications that
generate large amounts of data in intelligent cyber–physical systems (ICPS). Though FL can …

Federated learning (FL) allows multiple edge computing nodes to jointly build a shared
learning model without having to transfer their raw data to a centralized server, thus …

To leverage massive distributed data and computation resources, machine learning in the
network edge is considered to be a promising technique, especially for large-scale model …