  Emerging technologies that generate a huge amount of data such as the
Internet of Things (IoT) services need latency aware computing platforms to
support time-critical applications. Due to the on-demand services and
scalability features of cloud computing, Big Data application processing is
done in the cloud infrastructure. Managing Big Data applications exclusively in
the cloud is not an efficient solution for latency-sensitive applications
related to smart transportation systems, healthcare solutions, emergency
response systems and content delivery applications. Thus, the Fog computing
paradigm that allows applications to perform computing operations in-between
the cloud and the end devices has emerged. In Fog architecture, IoT devices and
sensors are connected to the Fog devices which are located in close proximity
to the users and it is also responsible for intermediate computation and
storage. Most computations will be done on the edge by eliminating full
dependencies on the cloud resources. In this chapter, we investigate and survey
Fog computing architectures which have been proposed over the past few years.
Moreover, we study the requirements of IoT applications and platforms, and the
limitations faced by cloud systems when executing IoT applications. Finally, we
review current research works that particularly focus on Big Data application
execution on Fog and address several open challenges as well as future research
directions.
