As IoT expands, efficient data processing and low-latency service delivery are increasingly important. In fog computing, where resources are distributed at the network edge, optimal microservice placement is essential for resource utilization. Addressing challenges like limited computational power, energy constraints, and security, we introduce the Dynamic Fog Resource Allocation and Optimization (DFRAO) algorithm. DFRAO dynamically optimizes microservice placement by minimizing a multi-faceted cost function that accounts for latency, resource usage, energy consumption, and security. Continuously adapting to real-time conditions, DFRAO ensures QoS while maximizing efficiency. Evaluations against algorithms like GA, ACO, FFD, and PSO show DFRAO’s outstanding performance in reducing latency, optimizing resources, and enhancing energy efficiency. This paper presents DFRAO as a crucial tool for improving scalability, reliability, and overall performance in fog computing, essential for future IoT service delivery.