Cost Efficient Task Offloading for Delay Sensitive Applications in Fog Computing System

Fog computing has emerged as a promising solution to process tasks and computations generated by end devices. It enhances the quality of service for delay-sensitive applications using low-latency devices like fog to process data instead of a high-latency cloud environment. Thus, it becomes the need of the hour to schedule tasks effectively over fog nodes to minimize the overall cost of the system. In this paper, we are proposing a cost-efficient task-offloading method in a fog computing environment. The model uses a gateway to collect information from all the fog nodes and assigns tasks to the fog nodes in an efficient way. The objective of the work is to minimize the overall cost of the system in terms of energy consumption and makespan. The makespan consists of transmission time, processing time, and waiting time. The results obtained from the work are compared with that of the random scheduling and longest job fastest processor methods. The simulation results obtained from the proposed method are found to be superior to the other existing methods. The overall cost of the system is enhanced in an optimized way.