Optimizing the Performance of Fog Computing Environments Using AI and Co-Simulation

Abstract

This tutorial presents a performance engineering approach for optimizing the Quality of Service (QoS) of Edge/Fog/Cloud Computing environments using AI and Coupled-Simulation being developed as part of the Co-Simulation based Container Orchestration (COSCO) framework. It introduces fundamental AI and co-simulation concepts, their importance in QoS optimization and performance engineering challenges in the context of Fog computing. It also discusses how AI models, specifically, deep neural networks (DNNs), can be used in tandem with simulated estimates to take optimal resource management decisions. Additionally, we discuss a few use cases of training DNNs as surrogates to estimate key QoS metrics and utilize such models to build policies for dynamic scheduling in a distributed fog environment. The tutorial demonstrates these concepts using the COSCO framework. Metric monitoring and simulation primitives in COSCO demonstrates the efficacy of an AI and simulation based scheduler on a fog/cloud platform. Finally, we provide AI baselines for resource management problems that arise in the area of fog management.