EVALUATING THE EFFICIENCY OF FOG COMPUTING ON THE INTERNET OF THINGS USING A NON-MARKOV MODEL

Abstract

As new technologies appear and submerge with each other, people get more and more dependent on them, and as more and more different devices connect with each other, the more important it gets to reach accurate decisions in the fastest possible way. With nowadays self-driving cars and other similar technologies it is most important to connect many different sensors and devices together and make them communicate and reach a decision as fast as possible. The article discusses a scenario in which several different sensors and devices on the Internet of things are connected together in a fog computing system for quick decision making. To estimate the efficiency of fog system, The non-Markov model of multichannel system of mass service with "heating" and "cooling" is proposed. It allows to take into account the peculiarities of the organization of fog calculations and calculates the waiting time before making a decision and after it. Another feature of the model is that it allows in many cases to improve the accuracy of the initial data set compared to the non-Markov model. A simulation is made and the model results are presented graphically and showed how Warm-up and cooling have great influence on the efficiency of fog computing and how the waiting time of each response is multiplied.