“Fog-Miner” Based Resource Aware scalable Framework Development in IoT platform

Fog computing is a system framework, distributed in nature and reduces latency in data communication between the Internet of Things (IoT) and cloud networks. The present state of the art focuses on the data communication and incorporation of blockchain in fog networks. Very few researches are there on the creation of fog networks and there exists no systematic study to estimate fog resources for the IoT sensor traffic. In this paper, we have theoretically modelled the requirement of fog resources for the sensor traffic in the IoT system, in terms of System Utility estimation using the Queueing theory model. We have embedded the miner nodes of the blockchain framework with the fog layer to make the whole network transparent to all the users. Here, we have performed an experimental analysis based on the proposed framework(fog miner) to determine the system response time and performed simulation using the IFogSim simulator to estimate the energy consumption of the framework. We also estimate the influence of sensor nodes addition on the system utility for the proposed framework. The experimental and theoretical analysis emphasises the scalability issues of the framework and it gives better performance than the present state of the art research.