Research on Proactive Service Discovery using Fog Computing focuses on designing intelligent mechanisms to predict, identify, and provision services at the network edge before they are explicitly requested by users, thereby reducing latency and improving Quality of Service (QoS) in distributed environments. This area addresses challenges related to dynamic resource availability, mobility of devices, heterogeneous network conditions, and real-time service requirements. Key research directions include predictive service caching and prefetching strategies, context-aware and workload-aware service discovery algorithms, and machine learning–driven models for anticipating user requests. Other emerging topics involve multi-objective optimization balancing service availability, latency, and energy consumption, edge–fog–cloud collaborative discovery frameworks, and decentralized or peer-to-peer service discovery protocols. Additionally, research on adaptive, fault-tolerant, and scalable service discovery mechanisms, integration with IoT applications, and privacy-preserving proactive discovery represents significant avenues for advancing efficient and intelligent fog computing systems.