Enhancing Energy Efficiency in Car Parking Systems through Fog Computing Architecture

The automotive industry is seeing rapid growth as a result of an increase in the number of vehicles, as never seen before. This is leading to several issues, like traffic jams, more time spent in commuting between places, environmental issues, and excessive fuel consumption. A number of the studies have offered suggestions on smart parking solutions that leverage the cloud infrastructure side. Still, energy consumption is one of the important issues for cloud-based applications, especially in smart transportation systems, as high energy usage leads to increased operational costs and environmental impact. Fog computing, also known as edge computing, is a distributed computing system that stores data and processes information between the cloud and the data source. It can provide a remedy to the situation by placing cloud resources closer to users, thereby applying load balancing which offers reduced energy consumption and benefits such as on-demand scalability, resource mobility, and improved security. Thus, the primary purpose of employing fog computing with load balancing is to reduce energy consumption and relieve operations costs and environmental impact in the smart parking system. This paper focuses on evaluating the effectiveness of the proposed method through simulations conducted on iFogSim. The evaluated results show that the load balancing in the fog computing approach resulted in a 65-70 % improvement in the overall system in terms of reduced energy consumption of edge devices.