Multi-objective Optimization for Dynamic Service Placement Strategy for Real-Time Applications in Fog Infrastructure

Abstract

Fog computing is rising as a dominant and modern computing model that thrives on delivering Internet of Things (IoT) computations. It is an addition to cloud computing, helping it handle services needing a faster response. A well-built dynamic service placement strategy could improve fog performance. This paper proposes a dynamic service placement strategy in a fog infrastructure for real-time applications. The main idea of this work is to perform a multi*objective optimization on response time and available resources in fog networks. Hence, depending on the fog node's response time and available computational resources, the algorithm will choose the fittest node to send the service in real-time. Finally, we model and evaluate our proposed strategy in the iFogSim-simulated Fog infrastructure. Results of the simulation studies demonstrate significant improvement in response time and resource utilization over several other strategies, improving the fog network's performance.