Smart Resource Scheduling Model in Fog Computing

Abstract

Fog computing is among the most significant new concepts in recent technological advancement. It addresses various issues of cloud computing by delivering compute, connectivity, storage, and actual services closer to end devices. Conversely, as systems become more automated, the number of task executions by fog devices grows, necessitating the inclusion of more fog devices. In this paper, we suggest a smart Scheduling framework that enhances the usage of current resources instead of installing more fog sources. It has an extra layer called Master Fog (MF) between each of the cloud and specific fogs termed Citizen Fog (CF). The MF is in a better position to decide on CF and cloud deployment. The Comparative Attributes Algorithm (CAA) is used to prioritize jobs, and a Linear Attribute Summarized Algorithm (LASA) is used to choose the most accessible CF with the greatest computing capabilities. The final findings demonstrate a significant reduction in energy consumption compared to the basic design in order to reach the best network efficiency, as well as important advantages represented in the increase of bandwidth availability and efficient utilization of other sources.