Hybrid Optimization of Data Replication in Mobile Edge Computing using Flower Pollination and Simulated Annealing to Minimize IoT Latency

Mobile Edge Computing or MEC is one such paradigm that can be useful in making improvements in IoT networks and decreasing the latency. The rising IoT applications that call for low latency in application point to the challenge of data replication. The purpose of this study is to find the most suitable approach to utilize FPA and SA in reducing IoT latency. Implementation of FPA and SA results in efficient local search and also the exploration of the entire solution space. These two algorithms improve the replication of data solutions in a MEC environment. The proposed approach, therefore, aims at placing data and replicating it appropriately at different MEC nodes to minimize total latency within IoT networks. In regards to different aspects such as reduction in latency, the amount of resources employed, overall system efficacy, the result of the simulations suggest that the hybrid approach surpasses the conventional approaches on a regular basis. This work fits into the current literature on MEC by proposing a feasible solution to the novel question of latency in IoT networks apart from providing guidance on how to use MEC in real-world applications. Furthermore, it provides a feasible approach to future MEC networks and increases the perceived satisfaction in applications with high latency constraints like IoT.