Boosted Performance, Quick Response, and Better QoS Using IoT Plus

keywords: Fog computing revolution, processing time, speed, reliability, bandwidth drop, traffic congestion, priority-based scheduling packets, IoT application priorities
The Internet of Things (IoT), as a concept, was not officially named until 1999 where it was still used by big computer and communication companies. It is the connection between objects anywhere, anytime, using internet communication. IoT is one of the network concepts which are growing rapidly in the last few years. The connected devices reach billions which leads to a huge increase in data transfer through the network. This rapid increase of transferred data is overloading network servers which result in more processing and routing time. Fog computing and cloud computing paradigms extend the edge of the network, thus enabling a new variety of applications and services. In this research, we focus on the processing and routing time, moreover, we present a new model in the application layer of the IoT system to classify IoT applications according to their valued data. Also, we work on modeling the fog computing architecture and use the cell operator as the main fog center to store data and compare its performance with the traditional model. We present a comparative study with the traditional IoT architecture based on classifying applications and define a priority for each application. We aim to give solutions to lower data transmission time, reduce routing processes, decrease internet usages, increase response speed, deliver important and sensitive data first, improve the quality of services, enhance the overall performance of IoT systems by depending on fog network as the main layer for processing and storing data, then by giving each application a priority value to be served according to it where the application with the highest priority is served first on the network. Our method which is based on static priority shows better performance and management against the RWS and DRAG method which are based on many parameters to take a decision.
reference: Vol. 41, 2022, No. 1, pp. 330–356