The integration of serverless edge computing and the Industrial Internet of Things (IIoT) has
the potential to optimize industrial production. However, cold start latency is one of the main …

Serverless edge computing decreases unnecessary resource usage on end devices with
limited processing power and storage capacity. Despite its benefits, serverless edge …

Serverless edge computing has emerged as a new paradigm that integrates the serverless
and edge computing. By bringing processing power closer to the edge of the network, it …

Abstract The Industrial Internet of Things (IIoT) integrated with cloud computing resources
offers effective advancements in the field of industrial automation with open connectivity and …

Due to Industry 4.0, machines can be connected to their manufacturing processes with the
ability to react faster and smarter to changing conditions in a factory. Previously, Internet of …

The newest cloud computing approach, serverless computing, makes it easier to design
applications. Developers may avoid managing the servers by embracing and utilizing 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 …

Machine learning (ML) plays a key role in Intelligent Industrial Internet of Things (IIoT)
applications. Processing of the computation-intensive ML tasks can be largely enhanced by …

The Internet of Things (IoT) merges physical and virtual realms, whereas Mobile Access
Edge Computing (MEC) facilitates various IoT applications in this context. Machine Learning …

The demand for improving productivity in manufacturing systems makes the industrial
Internet of things (IIoT) an important research area spawned by the Internet of things (IoT). In …