Research on Cloud–Fog Collaborations focuses on designing integrated architectures and strategies that combine the centralized processing power of cloud data centers with the low-latency, edge-proximate capabilities of fog nodes. This area addresses challenges such as efficient workload distribution, latency-sensitive application execution, resource heterogeneity, and dynamic network conditions. Key research directions include task offloading and scheduling strategies across cloud–fog layers, collaborative resource allocation, and data placement optimization to minimize latency and bandwidth usage. Other emerging topics involve multi-objective optimization balancing QoS, cost, and energy efficiency, adaptive orchestration frameworks for cloud–fog synergy, and predictive analytics for proactive workload management. Additionally, research on fault-tolerant, secure, and privacy-preserving cloud–fog collaborative frameworks, edge–cloud–fog integration for IoT applications, and container- or microservices-based hybrid deployments represents significant avenues for advancing intelligent, efficient, and scalable cloud–fog computing systems.