Research in the Internet of Things (IoT) conceives a world where everyday objects are
connected to the Internet and exchange, store, process, and collect data from the …

The emergence of real-time and data-intensive applications empowered by mobile
computing and IoT devices is challenging the success of centralized data centers, and …

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a
great extent. To support the computational demand of real-time latency-sensitive …

Abstract In Internet of Things (IoT) data processing, cloud computing alone does not suffice
due to latency constraints, bandwidth limitations, and privacy concerns. By introducing …

Fog computing was designed to support the specific needs of latency-critical applications
such as augmented reality, and IoT applications which produce massive volumes of data …

Recently, the wide adoption of Internet of Things (IoT) devices has introduced new
challenges that the current cloud-centric approach must overcome. The high-latency …

With the success of the Internet of Things (IoT) and the widespread availability of mobile
devices, the traditional centralized cloud computing is facing severe network challenges (eg …

Fog computing promises to extend cloud computing to match emerging demands for low
latency, location-awareness and dynamic computation. It thus brings data processing close …

The recent increase in the number of Internet of Things (IoT) devices has led to the
generation of a large amount of data. These data are generally processed by cloud servers …

Hardware accelerators are available on the cloud for enhanced analytics. Next-generation
clouds aim to bring enhanced analytics using accelerators closer to user devices at the edge …