Research Challenges in Job Scheduling and Resource Distribution Methodology for Cloud Fog Atmosphere: An Organized Analysis

The IoT technology applications have become the most important technologies used internationally to encourage communication between humans and objects and enhance quality of life in recent years. This will lead to an increase in the variety of devices used in such applications, which will produce massive amounts of data. In 2012, Cisco made the first mention of fog computing, which sits between individual consumers (IoT devices) and cloud computing. Fog computing enhances cloud computing’s effectiveness, lessens its drawbacks, and offers storage and processing capacities at the edge, despite the fact that it is not a cloud computing solution. Resource management has a significant role in determining how well fog computing performs. Scheduling is essential to manage supplies in fog layer, which is the capability to match jobs to the suitable useful resources. As we know that the job is a minor component with a bigger undertaking with a deadline. Fog computing leverages distributed and heterogeneous resources, making task scheduling challenging. Numerous recommended scheduling algorithms have been produced in previous years; the maximum of them were engaged in scalability to fog computing. This study’s major goal is to extensively examine and evaluate the most important existing scheduling approaches in terms of their main context, advantages, limitations and performance measures. The analysis is presented in proportion of categories of algorithm and usage of parameters for measure of performance in fog.