The massive onsite data produced by the Internet of Things (IoT) can bring valuable
information and immense potentials, thus empowering a new wave of emerging …

Abstract Advancements in Internet and Telecommunications (ICT) accelerated the large-
scale deployments of IoT applications including smart city, smart healthcare, and smart …

Distributed computation and AI processing at the edge has been identified as an efficient
solution to deliver real-time IoT services and applications compared to cloud-based …

Edge and Fog computing paradigms overcome the limitations of cloud-centric execution for
different latency-sensitive Internet of Things (IoT) applications by offering computing …

A comprehensive guide to Fog and Edge applications, architectures, and technologies
Recent years have seen the explosive growth of the Internet of Things (IoT): the internet …

Current IoT trends reveal an increase in computational requirements for data processing.
Traditionally, data from sensors was uploaded to compute nodes at a backend cloud …

Edge Computing harnesses resources close to the data sources to reduce end-to-end
latency and allow real-time process automation for verticals such as Smart City, Healthcare …

Cloud computing has emerged as a new paradigm of computing, in which scalable and
virtualized resources are dynamically provided (anytime, everywhere, and in a transparent …

Data stream processing is an attractive paradigm for analyzing IoT data at the edge of the
Internet before transmitting processed results to a cloud. However, the relative scarcity of fog …

Edge computing is a fundamental enabler for the proliferation of the Internet of Things (IoT).
Resources, including compute and storage, are increasingly located at the edge of the …