… will be deployed at the edge of wireless networks. This trend has generated strong interest
in realizing an “intelligent edge” to support AI-enabled applications at various edge devices. …

… edge device is proposed. Based on the description and model construction of the distributed
task scheduling problem and machine learning… performance in intelligent edge computing, it …

… technology to achieve intelligent IIoT. To realize novel intelligent applications of edge-enhanced
IIoT, ML methods are proposed to improve the cognitive ability of edge intelligent IIoT in …

… intelligence (AI) is a kind of technology that endows the machine with certain intelligence so
that the machine … in the past decades, we mainly focus on machine learning (ML), a recently …

… Deploying machine learning systems on such edge … where machine learning systems have
been deployed at the edge of … used in successful applications of intelligent edge systems. …

… We argue that edge intelligence is expected to arise in the … that stem from pushing the
intelligence to the cloud and also … and utilising the opportunities edge intelligence has to offer. …

… intelligence on end devices using machine learning algorithms. Deploying machine learning
on such edge … that guarantee the execution of machine learning models on hardware with …

… of machine learning algorithms at the network edge. One of the key motivations of pushing
machine learning toward the edge is … To this end, we propose an intelligent edge computation …

… We consider an edge ML system as shown in Fig. 1, where an intelligent edge server
attached to a BS with N antennas is serving K single-antenna users, each with an ML task. The …

… , edge and cloud with machine learning (ML) provides us with collaborative intelligence and
… of the motivation to move the learning aspects of the ML algorithm to the edges as there are …