Cognitive management framework for fog computing in IOT case study: Traffic control system

Abstract

Fog computing is a new computational paradigm proposed by Cisco that subdues the shortcomings of cloud computing by transferring some of the core functions of cloud towards the network edge. Internet of Things (IOT) is a very promising technology, which are used heavily in many areas of life and with such a large and rapid spread produces a lot of challenges in IOT. As reported by Cisco, by the year 2020, the next generation Internet-connected devices would comprise of around 50 billion Internet-connected devices which are located at the edge of the network and require support for mobility, low latency, real-time, and location-aware services. The Cloud computing is used as a main component in IOT architecture to provide processing and storage services for IOT system but the conventional cloud computing architecture is completely centralized in nature, and therefore, fails to provide real-time and low latency services to billions of IOT devices at the edge of the network, simultaneously. The main objective of this research is to combine the capabilities of Fog Computing, Cognitive and Context-Aware IOT to build a cognitive management framework for Fog computing capable of adopting it's behavior in a context-aware fashion to maximize the number of functions that can be carried out in The Fog and to provide a solution for determining which functions should be carried out in the Fog and which should be carried out in the cloud and how the Fog should interact with the Cloud, The same function in some situations can be carried out in the fog while in other situations can be carried out in the cloud according to its context.