SDN-based optimal task scheduling method in Fog-IoT network using combination of AO and WOA

Fog computing (FC) is an emerging paradigm developed to increase the speed of data processing in the Internet of Things (IoT) system. In such environment, an optimal Task Scheduling (TSch) of IoT devices requests can improve the performance and performance of IoT systems. This chapter introduces a task requests scheduling method in an IoT-Fog System (IoTFS) based on Software Defined Networks (SDN) for two reasons. The first reason is the fully flexible infrastructure virtualization that uses the IoT-Fog network's TSch capabilities to work on an active platform. The second reason is to reduce latency for IoT devices. An SDN-IoT-Fog computing model is proposed, which reduces network latency and traffic overhead by using a centralized IoTFS controller and coordinating network elements in the SDN controller layer. So, a hybrid Meta-Heuristic (MH) algorithm using the combination of Aquila Optimizer (AO) and Whale Optimization Algorithm (WOA), which is called AWOA, is proposed to schedule IoT task requests and allocate FC resources to IoT task requests to reduce the task completion time of IoT devices. The purpose of the proposed SDN-based AWOA method is to optimize task Execution Time (ET), Makespan Time (MT), and Throughput Time (TT), which are investigated in this chapter to the Quality of Services (QoSs). Experiments show that the proposed SDN-based AWOA is stronger than the compared algorithms for different Evaluation Metrics (EMs).