Resource monitoring and management services together play a vital role in improving the overall performance of fog computing services. The monitoring system continuously keeps track of all resources by collecting and analyzing the status information and alerts the user when the performance decreases. Resource management involves load balancing, resource scheduling and allocation, and it requires accurate resource status which is provided by a resource monitoring system to take scheduling and allocation decisions. The resource management activities are NP-hard problems and require optimal techniques to improve resource utilization and reduce energy consumption and latency. This paper proposes a resource management model using improved bio-inspired algorithms and a fog monitoring model to improve resource utilization and reduce energy consumption. The simulation results show that the proposed model is effective in terms of execution time, response time, and energy consumption compared to the state-of-the-art technique