With the global outbreak of COVID-19, the Internet of Medical Things (IoMT), as an extension
of the Internet of Things (IoT), has received increasing attention due to its ability to remotely …

Federated learning (FL) enables multiple devices to collaboratively train a shared machine
learning (ML) model while keeping all the local data private, which is a crucial enabler to …

In this paper, we devise an efficient and flexible management for mobile edge computing
(MEC)-aided industrial Internet of Things (IIoT), from a federated learning approach. In the …

Recently, we have witnessed the evolution of Edge Computing (EC) and Deep Learning
(DL) serving Industrial Internet of Things (IIoT) applications, in which executing DL models is …

The Internet of Things (IoT) is widely regarded as a key component of the Internet of the
future and thereby has drawn significant interests in recent years. IoT consists of billions of …

The accelerating convergence of artificial intelligence (AI) and Internet of Things (IoT) has
sparked a recent wave of interest in Artificial Intelligence of Things (AIoT). By exploiting the …

Many industrial processes have been transformed by ict infrastructure. Artificial intelligence
and machine learning algorithms have been needed by companies of all sizes, whether …

In the Industrial Internet of Things (IIoT), model and computing power sharing among
devices can improve resource utilization and work efficiency. However, data privacy and …

In this article, we propose a lightweight blockchain-inspired framework-Magnum-as a
magazine of transfer learning models in blocks. We propose the storage of these blocks on …

Large Machine Learning (ML) models require considerable computing resources and raise
challenges for integrating them with the decentralized operation of heterogeneous and …