Multi-Level Fog Based Resource Allocation Model for EVs Energy Planning in Smart Grid
The 43nd IEEE Conference on Local Computer Networks (LCN)
n order to optimally schedule electric vehicles (EVs) energy charging and discharging demands, we propose in this paper a multi-level fog (MLF) model architecture. EVs energy demands in MLF are planned as charging and discharging calendars to handle with EVs energy demands in smart grid environment. Our work integrates a priority queuing model based on markov chain analysis to schedule EVs energy calendars and allocate computing resources. Furthermore, we use the distributed feature of fog networks to cover micro grids. To this end, and to ensure the efficiency of resources allocation, we further propose two workload placement mechanisms for smart grid environment. Extensive simulations are performed under accurate assumptions and realistic environment based on real energy loads in the city of Toronto. The obtained results indicate the efficiency of the proposed MLF mode.