IoT Data Placement in the Fog infrastructure with mobile devices

Abstract

With the growth of the worldwide number of IoT devices, finding the right placement and storage of the massive created data is a major challenge. In fact, most IoT applications are time-sensitive applications implemented in critical sectors where any delay can hinder their decision-making, operational execution and decrease their performance. Fog Computing is a better solution to reduce latency by storing and processing real-time data locally on the edge network. Efficient placement strategies are required to map data to distributed infrastructure nodes. Current solutions do not consider the mobility of IoT devices which exists in almost all the real systems. In this paper, we use the random waypoint model to shape the mobility of an IoT system. Furthermore, we formulate our data placement using multiple replicas as a multi-objective linear programming problem aimed at minimizing the overall system latency and the number of data replicas. Then, we propose a greedy heuristic algorithm for IoT devices mobility modeling and data assignments in a feasible time. It uses a refined method to filter possible solutions in order to find the final solution with minimum overall latency while fulfilling producer data storage resource requirements and taking into account data sharing between the distributed consumers in Fog infrastructure. We conducted the experiments with iFogSim simulator respecting two data consistency models for data replicas synchronization. The results show that the proposed data placement strategy improves significantly the overall system latency and the number of data replicas to use.