Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

Fog computing is a paradigm that brings computational resources and services to the
network edge in the vicinity of user devices, lowering latency and connecting with cloud …

The Internet of Things (IoT) has been deeply penetrated into a wide range of important and
critical sectors, including smart city, water, transportation, manufacturing, and smart factory …

Conventional machine learning approaches aggregate all training data in a central server,
which causes massive communication overhead of data transmission and is also vulnerable …

With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …

The extensive propagation of industrial Internet of Things (IIoT) technologies has
encouraged intruders to initiate a variety of attacks that need to be identified to maintain the …

Fog nodes are implemented near to end‐users Internet of Things (IoT) devices, which
mitigate the impact of low latency, location awareness, and geographic distribution …

Driven by an unprecedented boom in artificial intelligence (AI) and Internet of Things (IoT),
edge intelligence (EI) pushes the frontier of AI from cloud to network edge, serving as a …

Fog computing (FC), extending cloud services to the network edge, has emerged as a key
paradigm for low-latency applications like the Internet of Things (IoT). However, efficient …

The fog computing concept was proposed to help cloud computing for the data processing of
Internet of Things (IoT) applications. However, fog computing faces several challenges such …