Energy Efficient Fog Computing with Architecture of Smart Traffic Lights System
Yawen Luo, Yuhua Chen, Junchao Wu · 2021
Energy efficiency has gained great attention recently for its economic values, requirements of green industry, and high-performance of smart systems. Compared to cloud computing, newly evolved fog computing is still in its infancy. Over the past few years, the fog computing concept, architecture, fog nodes definition, services broker algorithm, low-latency characteristics have been intensively studied; however, the literature about the energy consumption of fog computing is still rather limited. In this paper, we propose a fog computing based Smart Traffic Lights System architecture, and then study fog computing energy consumption by comparing it with cloud computing. Apart from the most literature which was built on theoretical analysis and/or experiments under limited settings, we conduct dynamic modeling and perform the simulation with the iFogSim simulator. Our results show that fog computing does save energy when compared to cloud computing under various considerations.