Optimizing Resource Allocation for Energy Efficiency in Fog Cloud Computing Environments

Fog computing has become the primary computing paradigm for IoT applications as it meets the low-latency needs of the growing number of IoT applications. However, the servers can get overwhelmed due to the high demand for fog resources in several IoT applications. Fog computing complements cloud computing, as it only processes user requests near them. Distributing tasks evenly across all nodes in the fog layer helps achieve optimal task processing. Load balancing in the fog-cloud computing environment aids in diminishing energy use. In this article, fog computing architecture named "EcoFogLoad Architecture" has been proposed to balance the workload among the fog layer. Along with this, the "Energy-Efficient Workload Optimization (EEWO)" algorithm has been proposed to optimize the use of resources at fog layer in terms of cost, time delay and energy consumption. iFogSim has been used to execute the proposed algorithm and obtain the experimental results. The results of the proposed approach are compared with those of other existing algorithms. Load balancing at the fog layer facilitates optimal resource utilization, reducing latency and improving service quality. The article concludes by presenting potential avenues for future research.