All one needs to know about fog computing and related edge computing paradigms: A complete survey

TL;DR: A layered FHC that leverages Linux utilities and bash-shell programming is implemented that provides deep insights into the performance of well-known big data databases, such as Cassandra, MongoDB, Redis, and MySQL, when deployed on a FHC.

TL;DR: In this article , the authors present a latency simulator for the Internet of Things (IoT), where the end-user can model the maximum and minimum latency, as well as the latency distribution (e.g. Gaussian) that each of the nodes might experience when interacting with each other.

TL;DR: The concepts of cloud computing and fog computing will be explored in this paper, and their features will be contrasted to determine the differences between them.

TL;DR: In this paper, an architecture that utilizes edge servers to allocate logistic jobs to autonomous guided vehicles (AGV) in smart factory setting is proposed, which can reduce computation load at main server when utilizing edge servers and the number of AGVs can be adjusted to achieve better job allocation and execution performance.

TL;DR: The clouds are clearing the clouds away from the true potential and obstacles posed by this computing capability.

TL;DR: The definition of edge computing is introduced, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge Computing.

TL;DR: This paper argues that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).

TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management is provided in this paper, where a set of issues, challenges, and future research directions for MEC are discussed.