Cloud computing is the delivery of computing services over the Internet. However, due to various limitations, fog computing was introduced. Fog computing is a mechanism that improves cloud computing capabilities by enhancing low latency for applications in smart cities, autonomous vehicles, and healthcare monitoring. This paper depicts a refined framework on resource allocation utilizing double auction mechanisms to enable dynamic pricing and real-time resource distribution. Our approach efficiently shows and manages the competition between providers and consumers by applying game-theoretic principles. The simulations demonstrate the improvements in resource utilization, provider profits, and user satisfaction metrics while a comparative analysis with baseline methodologies highlights these enhancements across 100 auctions. The fluctuating supply, the double auction mechanism, and its adaptability significantly improve the system’s resource allocation, utilization, and overall performance. Simulation results also show notable enhancements in QoS metrics, particularly enhancing latency-sensitive applications such as virtual reality and industrial IoT. The model accessibly manages the complexities of fog computing while ensuring equitable resource availability. Our insights validate the double auction mechanism as a transformative solution for resource management in fog computing to achieve optimal performance across diverse use cases while maintaining service quality among all.