Fog Computing for Efficient Predictive Analysis in Smart Grids
Rituka Jaiswal, Reggie Davidrajuh, S. M. Wondimagegnehu · 2021
The traditional centralized Cloud system for data processing is ineffective due to high application latency, data security issues, big data issues, and so on. Current Smart Grid sensors are producing huge amount of data and therefore need Fog Computing for real-time decision making. In this paper, we propose a Fog Computing architecture for executing a Smart Grid application. We use a crucial application of Smart Grid, which is future power consumption forecasting for processing on Fog and Cloud platforms. Also, to show the efficacy of Fog Computing for the power forecasting application, we measure and compare the run time and memory consumed on Fog and Cloud platforms. It is theoretically proved that Fog platforms performs better once the Fog network optimization is achieved.