Research on Green Fog Computing focuses on developing energy-efficient and environmentally sustainable strategies for managing computation, communication, and storage within fog environments. This area addresses challenges such as high energy consumption, carbon footprint reduction, and resource optimization in heterogeneous, distributed, and resource-constrained fog infrastructures. Key research directions include energy-aware task scheduling and resource allocation, power-efficient fog node operation, and dynamic voltage and frequency scaling (DVFS)-based energy management. Other emerging topics involve renewable energy integration into fog infrastructures, workload prediction for minimizing idle energy waste, and multi-objective optimization balancing energy, latency, and performance. Additionally, research on green service migration, thermal-aware fog node placement, carbon-aware fog–cloud collaboration, and machine learning-driven energy optimization represents significant avenues for advancing sustainable, intelligent, and eco-friendly fog computing ecosystems.