MAS‐aware Approach for QoS‐based IoT Workflow Scheduling in Fog‐Cloud Computing
Marwa Mokni, Sonia Yassa · 2022
This chapter presents the multi-agent system (MAS)-genetic algorithm (GA)-based approach for Internet of Things (IoT) workflow scheduling in Fog-Cloud computing, which aims to optimize makespan, cost and latency values. The proposed approach is based on MAS, taking into account the different quality of service (QoS) metrics. A multi-objective optimization method is adopted to create the IoT workflow scheduling solution by developing the GA. The chapter presents an MAS consisting of a set of agent types with a specific mission to meet. The GA is one of the widely used metaheuristics to solve multi-objective optimization problems by optimizing the QoS metrics of the workflow scheduling solution. Experimental results demonstrate that the MAS-GA-based approach for IoT workflow scheduling in Fog-Cloud computing generates a scheduling solution that optimizes the cost and latency values when maximizing the workflow task number in Fog resources.