Performance Evaluation of SDN-Assisted Fog Computing System with State-Dependent Service

The exponential growth of Internet of Things devices combined with the limitations of cloud computing in terms of latency and quality of service for time-sensitive applications led to the development of a new technology called fog computing. By lowering the effective distance between IoT/end-user devices and the cloud, fog computing gets around the limitations of the cloud. Fog computing confronts issues for remote job offloading. Fog computing focuses on optimizing task offloading. One of the key ideas of fog computing is task offloading, which reduces latency and increases system efficiency. This article presents a novel analytical model that investigates state-dependent service queuing systems and the effect of state-dependent service time on the system’s overall performance. We outline some of the properties of the system, and numerical evaluations and simulations demonstrate the validity of the proposed model. The evaluation findings indicate that the proposed model achieves an acceptable level of accuracy and makes it possible to offload tasks effectively in using SDN-assisted fog computing systems.