Theoretical modelling of fog computing: a green computing paradigm to support IoT applications

TLDR

Existing research on fog computing has mainly explored its principles and significance for IoT. The study aims to theoretically model fog computing architecture, mathematically define its components, and compare its performance with cloud computing. The authors develop a mathematical formulation of fog computing components and evaluate service latency and energy consumption against cloud computing. The analysis shows that fog computing, combined with cloud, is an efficient green platform for next‑generation IoT, reducing mean energy expenditure by 40.48 % for 25 % of real‑time low‑latency applications compared to conventional cloud.

Abstract

In this study, the authors focus on theoretical modelling of the fog computing architecture and compare its performance with the traditional cloud computing model. Existing research works on fog computing have primarily focused on the principles and concepts of fog computing and its significance in the context of internet of things (IoT). This work, one of the first attempts in its domain, proposes a mathematical formulation for this new computational paradigm by defining its individual components and presents a comparative study with cloud computing in terms of service latency and energy consumption. From the performance analysis, the work establishes fog computing, in collaboration with the traditional cloud computing platform, as an efficient green computing platform to support the demands of the next generation IoT applications. Results show that for a scenario where 25% of the IoT applications demand real-time, low-latency services, the mean energy expenditure in fog computing is 40.48% less than the conventional cloud computing model.