In recent times, the Internet of Things (IoT) applications, including smart transportation, smart
healthcare, smart grid, smart city, etc. generate a large volume of real-time data for decision …

Enabling data processing at the network edge, as close to the actual source of data as
possible, is a challenging, yet realistic goal to be achieved by the Internet of Things (IoT) …

Fog computing [1],[2], also known as edge computing, is an emerging Internet of Things (IoT)-
centric paradigm in which traditionally cloud-based data storage, computation, and control …

The wide spread deployment of smart edge devices and applications that require real-time
data processing, have with no doubt created the need to extend the reach of cloud …

A common design of the Internet of Things (IoT) system relies on distant Cloud for
management and processing, which faces the challenge of latency, especially when the …

When focusing on the Internet of Things (IoT), communicating and coordinating sensor--
actuator data via the cloud involves inefficient overheads and reduces autonomous …

Abstract Internet of Things (IoT) systems are expected to generate a massive amount of data
that needs to be processed. Given the large scale and geo-distributed nature of such …

Emerging IoT applications with stringent requirements on latency and data processing have
posed many challenges to cloud-centric platforms for Smart Cities. Recently, Fog Computing …

Fog computing is a horizontal, system-level architecture that distributes computing, storage,
control, and networking functions closer to the users along a cloud-to-thing continuum. This …

Fog Computing is an emerging paradigm, suitable to serve the particular needs of IoT
networks. It includes the deployment of computational devices at the edge of the network …