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