Network Usage and Time Efficient Performance Enhancement Model for IoT Applications in Fog Cloud Computing

Fog computing bridges IoT applications and cloud computing, providing low latency services through local computation and storage. Despite its advantages, challenges such as efficient scheduling and placement of IoT applications on fog cloud nodes hinder its widespread adoption. This manuscript presents a Performance Enhancement Algorithm for scheduling IoT applications in a fog cloud environment. The algorithm comprises four key procedures that schedule application modules across the available infrastructure devices. Merge sort along with the heterogeneous shortest module first strategy is used in fusion as the key to improve the performance. The effectiveness of this proposed algorithm was evaluated using the iFogSim simulator and the results demonstrate significant improvements, with total network usage improvement of 66.31% over HSMF, 88.40% over edge-wards, and 98.66% over the cloud-only method. Also, it improves the execution time significantly in most network configurations. Our research contributes to providing a very reliable means for placing applications in the fog-cloud infrastructure as our fusion algorithm makes it a very stable and scalable for CPU bound tasks in fog and cloud computing environment.