Improving Quality of Services of Fog Computing Through Efficient Work Flow Scheduling

A more complex technique named fog computing is aimed at resolving a number of issues with vast IoT networks. Fog Computing is likely to provide superior cloud services to mobile customers. Devices that are prone to complex computations and processing must use fog computing. Fog's major purpose is to bring data closer to users who are positioned at network edges by delivering it to specific locations. It is used when only selected data is needed to transfer to the cloud. The task of assigning workflow to the target system's devices in such a way as to provide an optimal schedule while balancing energy usage and make span minimization is known as workflow scheduling with in fog-cloud system. Workflow systems have such a wide variety of unique tasks and complex frameworks. Processing, entering, and gaining access to storage and software operations could be a part of every task. The Quality of Services (QoS) in fog computing is determined by the process of assigning resources to cloud clients, thus the cloud service provider must accomplish this as effectively as feasible. The findings have been compared to those obtained from the cloud-based model of the smart parking system, and this method is employed in iFogSim to mimic the parking system. According to the findings, the efficient parking system's proposed fog-based implementation successfully reduces latency. Furthermore, it has been discovered that, in contrast to the smart parking system's cloud-based implementation, the recommended fog-based implementation minimises total network consumption.